tech exam

TECHNOLOGY QUIZ STUDY GUIDE


1. SUSTAINABLE DEVELOPMENT GOALS

WHAT ARE THE SDGs

A set of 17 global goals adopted by the United Nations in 2015 as part of the 2030 agenda for sustainable development. They provide a blueprint for addressing the world's most pressing social, economic and environmental challenges to achieve a sustainable future for all


They are built upon the millennium development goals and cover a wide range of interconnected issues, including poverty, hunger, health, education, gender equality, clean water and sanitation, renewable energy, climate action and peace and justice


Action in one area will affect outcomes in others and development must balance social, economic and environmental sustainability 

1. No poverty

End all forms of poverty no matter sex and age. Systems and policies to protect the poor and needy

2. Zero hunger

End hunger worldwide. Ensure secure access to food and unkeeping nutrition. Sustainable agriculture

3. Good health and wellbeing

Ensure healthy lives, physically and emotionally. Lower mortality rates 

4. Quality education

Quality and free education to everyone. Adults get further education and training. Increase quality teachers

5. Gender equality

Equality for all girls and women. End discrimination and violence. 

6. Clean water and sanitation

Access to clean drinking water, sanitation, and hygiene. Protect water related ecosystems

7. Affordable and clean energy

Affordable, reliable and sustainable energy for all. Promote international cooperation for advanced clean energy technology

8. Decent work and economic growth

Sustainable econ growth and protection for fair, safe and decent employment. Prevent slavery and child labor

9. Industry, innovation and infrastructure

Build quality, resilient infrastructure and support small businesses. Promote innovation and access to technology

10. Reduce inequalities

Reducing inequalities for everyone and all social groups

11. Sustainable cities and communities

Have accessible housing, sustainable transport and disaster risk management

12. Responsible consumption and production

Ensure sustainable consumption and production patterns. Control use and managing of waste through policies and cooperation

13. Climate action

Act immediately to fight the climate crisis and adapt to impact. Promote awareness, policy change and support 

14. Life below water

Protect the ocean and marine life. Prevent pollution and overfishing

15. Life on land

Conserve and restore ecosystems. Prevent destruction of natural habitats and loss of biodiversity

16. Peace, justice and strong institutions

Build peaceful, inclusive societies with law and accountability at all levels. End violence, trafficking and corruption

17. Partnerships for the goals

Strengthen international cooperation and domestic support. Assist developing countries in sustainable development

WHY ARE THEY IMPORTANT

These goals, when achieved, promise to create a prosperous world and flourishing nature based around sustainability. Used to be a blueprint for a better future, but now, with growing unrest and acute climate crisis, the SDGs is a necessity to ensure the safety of our civilization

Addressing global challenges

Recognize that the world faces complex and interconnected challenges that require collective action

Holistic approach

Integrating social, economic and environmental dimensions of sustainable development. Emphasise the need for balanced and integrated solutions to promote economic growth, social inclusion and environmental sustainability

Universal scope

They are universal in nature, applying to all countries regardless of their development level

Leave no one behind

Ensure that progress is made to benefit all individuals and groups 

Partnerships and collaboration

Emphasise the importance of partnerships and collaboration between governments, civil society, private sector and other stakeholders

Monitoring and accountability

Include a robust monitoring and accountability framework to track progress and hold governments and stakeholders accountable for their commitments. Ensure transparency and promote action towards achieving these goals

USE OF TECHNOLOGY TO ACHIEVE SDGs

The power of technology

  • Technology is a revolution that has already changed many of our daily habits

  • If we employ technological innovation, we could make progress with two-thirds of the 169 targets within the sustainable development goals

  • We need to improve how we use data, technology and innovation to achieve our goals and create a positive impact

Approaching the sustainable development goals from a technology perspective

There are three possible ways that we can harness technology to achieve the sustainable development goals and create a better world

Replacement 

Use technologies that completely replace a manual process

Optimization 

Relies on technology to make a process more efficient by way of data or automation. 

Redesign 

About technologies that reinvent a product or service, which then create a new business model. Enables us to adapt our economic system to a more sustainable future and creates an opportunity to monitor and digest information about these projects through innovative technologies

Emerging technologies

  • There are many technological advances that we can use to analyse our impact on the world. 

  • Emerging technologies such as the internet of things, artificial intelligence and blockchain could accelerate progress towards the sustainable development goals

  • They can help us understand the needs of our biodiversity and the natural capital

  • When looking for climate solutions, we need to take a systemic approach

  • By combining the technology of business, the private sector, the public sector and startups, we can make great advancements in achieving the Sustainable Development Goals

  • Technology plays a crucial role in achieving the sustainable development goals by providing innovative solutions, improving efficiency and enabling widespread access to information and resources

Data and monitoring

facilitates data collection, analysis, and monitoring, which are essential for tracking progress towards the SDGs. Advanced data analytics, remote sensing technologies, and digital platforms help governments and organisations gather and analyse data on various indicators, allowing for evidence-based decision-making and targeted interventions

Access to education

Technology can enhance access to quality education, especially in remote and underserved areas. A main example is online learning platforms

Healthcare and telemedicine

improves healthcare delivery and access to medical services. Telemedicine enables remote diagnosis, consultation,and treatment, extending healthcare to remote areas

Renewable energy and climate action

Advancements in solar, wind,and hydroelectric power technologies have increased energy efficiency and reduced reliance on fossil fuels. Smart grids, energy management systems, andIoT devices help optimise energy consumption and support climate action efforts

Agricultural innovation

Technology can revolutionise agriculture and food systems to promote sustainability. Precision farming techniques, sensor-based monitoring, and data analytics optimise resource use, increase crop yields, and reduce environmental impacts

Financial inclusion

Technology enables financial inclusion by providing access to digital payment systems, mobile banking, and microfinance platforms.

Sustainable cities and infrastructure

Technology supports the development of smart and sustainable cities. IoT devices, data analytics, and intelligent infrastructure systems enhance resource management, transportation efficiency, waste management, and urban planning.

Collaboration and knowledge sharing

Technology facilitates collaboration and knowledge sharing among stakeholders working towards the SDGs

CHALLENGES AND OPPORTUNITIES OF USING TECHNOLOGY FOR SDGs

Challenges: 

Digital divide

Limited access to technology hinders the ability to leverage its benefits for sustainable development. Addressing the digital divide is crucial to ensure equitable access and inclusion

Privacy and security

Protecting personal information and ensuring data security are essential to maintain trust and mitigate risks of tech implementation

Skills and capacity building

The lack of digital literacy and technical capacity can impede the adoption and utilisation of technology for sustainable development

Cost and affordability

Ensuring affordability and exploring innovative financing mechanisms are important to overcome financial obstacles

Opportunities 

Innovation and solutions

Tech fosters innovation, enabling the development of new solutions to address complex challenges

Data driven decision making

Technology facilitates data collection, analysis,and visualisation, enhancing evidence-based decision-making. enable policymakers, organisations, and communities to identify priority areas, track progress, and allocate resources effectively.

Collaboration and partnerships

enables collaboration and partnerships among diverse stakeholders

Scalability and reach

offers scalability, allowing interventions and solutions to be deployed widely and reach underserved populations

Efficiency and resource optimization

improves efficiency in sectors such as energy, agriculture, and transportation, leading to resource optimization and reduced environmental impacts

Key technologies to foster SDGs

Renewable energy technologies

help reduce reliance on fossil fuels, mitigate climate change, improve access to clean energy, and promote sustainable development.

Internet of things

Connect physical objects and enable data exchange. IoT applications support smart infrastructure, energy management, water and waste management, and enhance efficiency, sustainability, and resource optimization

Artificial intelligence

AI can support healthcare diagnostics, enhance agricultural productivity, optimise energy systems, improve disaster response,and promote sustainable development.

Mobile and digital technologies

enable access to education, telemedicine, financial services, e-commerce, and information, bridging gaps and empowering individuals and communities.

blockchain

Blockchain can support anti-corruption efforts, secure supply chains, enhance governance, facilitate trusted transactions, and strengthen collaboration among stakeholders

Green technologies and circular economy

promote sustainable production and consumption patterns, reduce environmental impacts, and support the transition to a circular economy.

OPTIONAL MATERIALS

Agriculture success case

By leveraging technology, farmers can monitor crop conditions, optimise water and fertiliser usage, and minimise environmental impacts. Reduces resource consumption and promotes sustainable farming practices

Healthcare success case (mHealth)

Technologies enable remote consultations, health monitoring and health information dissemination. Healthcare providers can reach underserved populations, improve healthcare outcomes and enhance disease prevention and management

Transportation success case (electric mobility)

The widespread adoption of electric vehicles reduces reliance on fossil fuels by lowering carbon emissions. 

Textile and fashion success case (H&M)

embracing circularity and using technology driven solutions, leads to a reduction in waste, promotion of sustainable fashion and fostering of a circular economy

Financial services success case

Fintech solutions enable secure and convenient financial transactions, access to credit and financial services for unbanked populations


2. DIGITAL PRODUCTS AND DIGITAL TECHNOLOGY


Types of digital products


  • Software applications: computer programs, mobile apps or web applications

  • Digital media: forms of media that can be consumed digitally

  • Online courses and e-learning: educational resources provided in a digital format, delivered through learning management systems or online platforms

  • Digital subscriptions and memberships: digital products offering ongoing access or exclusive content to subscribers or members

  • Digital downloads: digital products that can be purchased and downloaded directly to a user's device

  • Virtual goods and in-game purchases: digital products take any form of virtual goods or in-game purchases

  • Software as a service: cloud-based software solutions accessed and used remotely over the internet 

  • Digital services: digitally delivered, digital marketing services or cloud based storage and backup services

EXPLAIN HOW DIGITAL TECHNOLOGY ENABLES THE CREATION AND DELIVERY OF DIGITAL PRODUCTS

Digital technology enables the creation and delivery of digital products through various mechanisms and capabilities.

Digital creation

Digital technology provides tools and software that enable the creation of digital products. These tools allow for efficient and flexible creation processes, enabling rapid prototyping, iteration, and customization. 

Digital storage and replication

Digital products can be uploaded to online platforms, websites, or cloud storage services, making them accessible to users worldwide. The internet facilitates the seamless delivery of digital products to end-users,regardless of their geographical location

Digital distribution platforms

These platforms provide a centralised and accessible marketplace for digital products. Content creators can showcase and sell their digital products directly to consumers, reaching a wider audience without the need for traditional distribution channels

Customisation and personalisation

Digital products can be tailored to individual preferences, allowing users to customise their experiences, settings, and interfaces. This flexibility enables users to personalise their interactions with digital products, providing a more engaging and tailored user experience 

Digital interactivity

Digital products can incorporate interactive elements such as user interfaces, multimedia content, virtual reality, augmented reality,and gamification which create a dynamic and engaging user experience

Overall,  digital technology revolutionises the creation and delivery of digital products by providing efficient creation tools, easy replication and distribution, global connectivity, customisation options and interactive capabilities


These advancements have transformed industries and opened up new opportunities for content creators and consumers in the digital landscape

ADVANTAGES AND DISADVANTAGES OF DIGITAL VS PHYSICAL PRODUCTS

Advantages of digital products: 


Convenience and accessibility: instantly accessed and delivered electronically, allowing users to enjoy them anytime, anywhere with an internet connection. This eliminates the need for physical storage, shipping or travel to access the product


Cost efficiency: digital products lower production and distribution costs compared to physical products 


Scalability and reproducibility: digital products can be easily reproduced and scaled to accommodate a large number of users without significant additional costs which allows business to reach a wider audience and generate more revenue


Easy updates and upgrades: Developers can release patches, bug fixes, or new features quickly, ensuring that users have access to the latest version of the product without the need for physical replacements or installations


Flexibility and customisation: digital products can be personalised to suit individual user preferences, allowing for a more tailored and engaging user experience

Disadvantages of digital products: 


Digital divide: This can limit the reach and accessibility of digital products,particularly in areas with limited connectivity or populations with limited digital literacy


Dependency on technology and infrastructure: This dependency can be a disadvantage when technology fails or when users lack the necessary devices for internet access


Potential for piracy and copyright infringement: Digital products can be susceptible to piracy and unauthorised distribution, potentially leading to revenue loss and intellectual property rights violations


Lack of tangibility: digital products lack physical presence or tangible attributes


Security and privacy concerns: Digital products can be vulnerable to security breaches and privacy concerns. Data breaches, hacking, or unauthorised access to personal information can undermine user trust and compromise sensitive data

Advantages of physical products


Tactile experience: Physical products offer a tangible and sensory experience that digital products cannot replicate


Perceived value: Some customers may associate physical products with higher quality or exclusivity, which can justify higher pricing or increase the perceived value of the purchase.


No dependency on technology: Physical products do not rely on technology or digital infrastructure for their functionality. Can be used without need of an internet connection


Physical ownership: Owning a physical product provides a sense of ownership and collection. These can be displayed, shared, or resold, creating a tangible connection between the product and the consumer

Disadvantages of physical products


Higher production and distribution costs: Physical products generally involve higher production and distribution costs compared to digital products


Limited reproducibility and scalability: Each physical unit requires individual production, packaging,and distribution, which can be time-consuming and costly


Inventory management and obsolescence: Overstocking or understocking can result in financial losses,and physical products can become obsolete if consumer preferences or market demands change.


Environmental impact: Physical products often require raw materials, energy, and transportation, contributing to environmental impacts such as resource depletion,pollution, and waste generation

IMPACT OF DIGITAL PRODUCTS ON SOCIETY

Impact on the economy

Increased productivity and efficiency

Digital products have led to increased productivity and efficiency in many industries. Automation, streamlined processes, and digital tools have allowed businesses to optimise their operations, reducing costs and enhancing productivity

New business models and industries

E-commerce platforms, digital marketplaces, and software-as-a-service (SaaS) models have created opportunities for entrepreneurs and startups to enter the market, fostering innovation and economic growth

Job creation and transformation

They have generated employment in areas such as software development, digital marketing, data analytics, and e-commerce logistics. However, they have also disrupted traditional industries, leading to job displacement in some sectors

Impact on culture

Global connectivity and communication

Digital products have connected people worldwide, enabling instant communication and collaboration across borders. Easier cultural exchange, idea sharing and virtual communication

Access to information and knowledge

Online libraries, educational resources, and search engines has made learning and research more accessible, bridging the digital divide and empowering individuals with information

Transformation of creative industries

Online platforms and streaming services have changed the way content is produced, distributed, and consumed. This has created new opportunities for artists, filmmakers, writers, and content creators, but also posed challenges related to copyright protection and fair compensation

Cultural preservation and digitization

Digitising books, photographs, artworks, and historical documents has enabled their wider accessibility, conservation, and protection from physical degradation

Emergence of digital media and entertainment

Streaming platforms, online gaming, and digital content creation have altered how people consume entertainment, leading to shifts in business models and revenue streams for the industry

  • Digital products have had a profound impact on the economy and culture

  • They have driven economic growth, innovation and job creation while fostering global connectivity, knowledge sharing and cultural exchange

  • They have also presented challenges such as job displacement, privacy concerns and the need for adapting legal frameworks to address emerging issues in the digital realm

Impact on environment

  • Digital products have the potential to contribute to environmental sustainability enabling remote work, reducing the need for commuting and, consequently, lowering carbon emissions

  • Digital media reduced the demand for physical goods, such as books and CDs, leading to a reduction in paper usage and plastic waste

  • the production and disposal of electronic devices can contribute to electronic waste, posing environmental challenges

  • Responsible e-waste management and sustainable manufacturing practices are crucial to mitigate these issues.

Impact on ethics 

  • The advent of digital products has raised ethical considerations that society must address

  • Privacy concerns have become prominent, with the collection and use of personal data by digital platforms

  • The ethical use of AI and automation has also garnered attention, as these technologies can impact employment, decision-making processes and biases

  • As society continues to navigate the digital age, it is crucial to strike a balance between harnessing the benefits of digital products and addressing the associated challenges to build a more inclusive, sustainable, and ethically conscious society

Impact on designing digital products

Design thinking

  • Design thinking is a non-linear, iterative process that teams use to understand users, challenge assumptions, redefine problems and create innovative solutions to prototype and test

  • It draws on the methods and processes of designers, such as sketching, prototyping, testing and iterating to understand the needs and desires of users and to generate innovative solutions that meet those needs

  • incorporates elements of psychology, sociology, engineering, business, and other disciplines to create products that are not only functional and usable, but also desirable and meaningful

  • based on the idea that design is not only a craft or skill, but also a way of thinking and reasoning that can be applied to any domain or problem

Agile

a project management approach that involves breaking the project into phases and emphasises continuous collaboration and improvement

User interface (UI)

the space where interactions between humans and machines occur. It includes the visual elements, such as screens, buttons, icons, etc., that users interact with when using a website, app, or other electronic device

User experience (UX)

the overall interaction and experience that users have with a product or service. It encompasses aspects of branding, design, usability, functionality, and performance. It is the process of creating products that provide meaningful and relevant experiences to users

These tools and methodologies are used in conjunction in the design of digital products: 

  • Design thinking is the foundation of the design process, as it provides a framework for understanding the problem and generating solutions

  • Agile Methods are the way of managing the project and delivering value to the customers in an iterative and adaptive way.

  • UI design and UX design are the outcomes of the design process, as they define how the product looks and feels to the users

  • Data storytelling is the process of translating data analysis into simple and understandable terms to influence a business decision or action

  • It can help communicate the value proposition and impact of the proposed solutions to internal stakeholders and users showcase deliverables of each agile sprint and design user interfaces that are intuitive, engaging and informative by incorporating rich data analysis, feedback and visualisations to the process


3. LOW CODE NO CODE TECHNOLOGY


  • Only 0.3% of the world’s population knows how to code

  • No code tools democratise the use of technology

  • Low code development will account for more than 65% of application development activity by 2024

OPPORTUNITIES

Main opportunities

  1. Productivity / agility

  2. Cost savings

  3. Collaborative


Seizing the opportunities

  • Delayed application development. 65% of organisations report delays in application development

  • Paper based processes. 37% of organisations still use paper for critical business processes

  • Accelerating innovation and digital transformation. 69% of organisations say accelerating digital innovation and transformation is the number one reason they adopted low-code application development

LOW CODE

  • Empowers business users to create their own solutions

  • Improves engineering resource allocation and scalability

  • Reduces development blockdogs

  • Delivers iterated solutions quickly

MAP OF NO-CODE TOOLS LANDSCAPE















IMPACT OF GENERATIVE AI ON NO-CODE

The proliferation of AI tools and startups can be seen as both a problem and an opportunity, depending on how it is approached. The abundance of AI tools and startups may present challenges, such as fragmentation and quality concerns, it also brings forth opportunities for innovation, specialisation, collaboration and market growth

* double check this


4. ARTIFICIAL INTELLIGENCE AND THE AI TOOL ECOSYSTEM


AI types based on capabilities: 

  • Artificial narrow intelligence (ANI) - narrow range of abilities

  • Artificial general intelligence (AGI) - on par with human capabilities

  • Artificial superintelligence (ASI) - more capable than a human

ARTIFICIAL GENERAL INTELLIGENCE (AGI)

  • AGI is a machine with general intelligence much like a human being to solve any problem as humans do in any given situation


AGI characteristics (those we see in all humans)

  • Common sense

  • Background knowledge

  • Transfer learning

  • Abstraction

  • Causality 


AI researchers and scientists need to find a way to make machines conscious, programming a full set of cognitive abilities

NATURAL LANGUAGE PROCESSING, UNDERSTANDING AND GENERATION

NLG

  • Discourse generation

  • Lexical choice

  • Sentence planning / generation

  • Realisation

  • Document structuring

NLP

  • Named entity recognition

  • Part-of-speech tagging (POS)

  • Symtactic passing 

  • Conference resolution

  • Machine translation

NLU

  • Lexical ambiguity / analysis

  • Sentiment analysis

  • Topic classification

  • Information extraction

  • Entity detection

  • Summarization

  • Semantic parsing

  • Syntactical analysis

APPLICATION MACHINE LEARNING

Examples:

ETHICS GUIDELINES FOR TRUSTWORTHY AI

Ensure that the development, deployment and use of AI systems meets the seven key requirements for Trustworthy AI:

  • Human agency and oversight

  • Technical robustness and safety

  • Privacy and data governance

  • Transparency

  • Diversity, non-discrimination and fairness

  • Environmental and societal well-being

  • Accountability 

THE AI DEBATE: DEVELOPMENT OF SUPER INTELLIGENT GENERAL AI

The beneficial AI movement

Digital utopians

  • Super intelligent AI will never come to pass (or in the remote future, too far)

  • Regulation could impede AI developments

  • AI could solve most problems, cures, diseases, extends life indefinitely and frees us from drudgery

  • AI systems must be robust and bug-free

  • Regulation to limit AI developments to avoid doomsday scenarios

  • Could we lose the ability to think for ourselves? Could we be denied the adventures of discovery and creativity? Could we be devalued, indoctrinated and lose freedoms, choices, emotions and experiences without even knowing it? Could we lose fundamental human rights including the right of self-determination, the right to work, to self-care, privacy and basic human dignity? What price utopia?


5. GENERATIVE AI


  • Generative AI describes algorithms that can be used to create new content, including audio, code, images, text, simulations and videos

  • Generative AI refers to AI techniques that learn a representation of artefacts from data, and use it to generate, brand new, unique artefacts that resemble but don't repeat the original data

  • Generative AI leverages sophisticated algorithms to produce fresh and original content

  • The applications of generative AI are wide ranging; it enables the creation of digital artwork and music compositions, as well as the generation of intricate 3D simulations for research and testing purposes

  • Gartner (2023) provides another perspective, emphasising the unique feature of generative AI: its ability to learn and comprehend the representation of artefacts from provided data 

  • This then forms the basis for the creation of entirely new and unique artefacts

  • This ability to generate new content comes from sophisticated machine learning techniques, which allow the AI to analyse and learn from existing data

  • These technologies allow AI to transcend its traditional role of simply processing and analysing data.

  • Generative AI can create, innovate, and even surprise us with the output it produces. As such, it opens vast new opportunities and challenges in the field of artificial intelligence.

TYPES OF GENERATIVE AI MODELS

Each model employs a unique methodology, embodies individual strengths and trade-offs, providing diverse avenues for the generation of new and compelling content. 

Generative adversarial network

  • A type of machine learning model that uses deep learning techniques to generate new data based on patterns learned from existing data. Once the generator is trained, you can use it to create new, synthetic data that is similar to some existing real data. 

  • The Generator's role is akin to that of an artist, taking in what is known as a latent variable, or a random variable that we can't directly observe but is significant for the domain of the data we wish to generate

  • From this random input, the Generator creates new, synthetic data that mirrors certain aspects of the real data. 

  • The Discriminator is a binary classifier, acting as an art critic that evaluates the authenticity of the Generator's creations, classifying whether the data presented to it is real (from the actual dataset) or fake (created by the Generator).

Variational autoencoders (VAEs)

  • A type of machine learning model that learns to reproduce its input and map data to latent space, which contains a compressed representation of the input data

  • Once trained, VAEs can generate new, synthetic data that is similar to the input data by randomly sampling points from the latent space and decoding them

  • VAEs comprise two critical parts: an encoder and a decoder. The encoder takes the input data and compresses it into a compact form in the latent space. Following this, the decoder takes the compressed data and reconstructs the original data as accurately as it can from this lower-dimensional representation

  • Variational Autoencoders, with their robust and dynamic nature, serve as a fundamental approach to generative modelling, providing the ability to create a diverse array of realistic outputs based on a set of input data

Diffusion models

  • A kind of machine learning model that uses a process of gradual change to turn a simple known type of random information into another type of information that we’re more interested in. this process happens in stages and goes in reverse order, similar to how heat spreads through an object

  • Once the model is trained, it can make new data that looks the data it learned from quite precisely

  • The core concept in Diffusion Models involves taking a starting point of randomness and gradually applying changes, stage by stage, to this initial state until it morphs into a

  • structured output that resembles the training data. 

Transformer-based models

  • A transformer-based model is a type of machine learning model that employs the concepts of self-attention and feed forwarding, meaning that numerically weigh the importance of each element in a sequence in relation to all others

  • Once a transformer model is trained, it can understand and generate data that is contextually similar to the training data, maintaining the structural and semantic properties of the input

  • These models harness the concepts of self-attention and feedforward neural networks, which enable them to numerically weigh the significance of each element in a sequence in relation to all the others

  • Transformer models don't process input data sequentially. Instead, they make use of their self-attention mechanism to analyse an entire sequence at once, creating a web of interrelations that link each element to every other element in the sequence

  • This method allows Transformers to capture complex relationships within the data, even over long distances, which was a notable shortcoming of earlier sequence models.

APPLICATIONS OF GENERATIVE AI

Text: large language models (LLMs) - open AI, chat GPT, google’s bard, etc

  • Large Language Models (LLMs) stand at the forefront of advancements in the field of Natural Language Processing (NLP), a crucial area in artificial intelligence. Leveraging the power of deep learning and transformer-based architectures, LLMs have demonstrated impressive capabilities in understanding and generating human-like text.

  • Despite their primary use in text generation, the flexibility of LLMs allows them to undertake a wide range of tasks

  • These include sentiment analysis, language translation,and text summarization, among others

  • They can be effectively used in a combination with traditional NLP techniques like text extraction, creating hybrid models that leverage the strengths of both machine learning and rule based approaches

  • These must be capable of capturing the sequential nature of text data, transformer based architectures are particularly effective in this regard due to their ability to account for long-range dependencies within the text data

  • These only have knowledge up to when they were last trained

Images: generative image models (GIMs) - mid journey

  • Generative Image Models (GIMs) need to be capable of capturing the inherent structure and intricate patterns within image data

  • They have significantly evolved over time, witnessing a major transition from GANsand VAEs to more recent Diffusion models (that offer a blend of the strengths ofGANs and VAEs)

  • They possess the remarkable ability to capture the inherent structure and intricate patterns within image data, allowing them to generate new images that maintain the characteristics of the training data yet exhibit their own uniqueness.

Multimedia: generative video and audio models (GVMs) and (GAMs)

  • Generative video models (GVMs) need to be able to comprehend the underlying temporal dynamics and spatial relationships within video data. Still young technology, but transformer-based models are emerging as a promising solution

  • Generative audio models (GAMs) are required to capture the time-sequential patterns and rick nuances within audio data. The very last models are using a combination of transformers-based + diffusion models with good results

  • The potential applications of GVMs and GAMs are indeed wide-ranging and exciting. They can generate synthetic videos for film and animation, create new music pieces, and even synthesise human-like speech

THE ECOSYSTEM OF GENERATIVE AI

  • Generative AI, with its capacity to create new, unique content, has given rise to a dynamic and evolving ecosystem. 

  • This ecosystem is diverse and encompasses hardware providers, software developers, data scientists, and application builders, all working in tandem to bring the vast potential of Generative AI into fruition.

  • Plugins are software components designed to add specific features to existing programs, enhancing their functionality and versatility

  • The context of Generative AI, plugins are facilitating more seamless integration of generative capabilities into a myriad of applications

  • This has allowed Generative AI to penetrate diverse domains and industries, significantly broadening its impact and utility

  • As we move forward, the ecosystem of Generative AI will continue to grow and diversify, bringing about exciting advancements and opportunities in AI technology

PROMPT ENGINEERING

An AI technique that involves crafting the input instructions to help LLMs understand the task they need to perform and elicit the desired response

Text prompts

A good prompt can contain the following elements. Not all appear in every prompt but if they do, it’s not important that they follow a specific order.

Role 

The AI model is given a specific role to guide its responses based on the knowledge, experience or perspective of a given expert or character or persona

Task description

This is where we give actual instructions to the model. For Example: “classify this text as X or Y”, or “change the tone

Examples 

It’s helpful to include examples (called shots) for the model to better understand the task. When we show the model one example, it’s called 1-shot prompting, and when more, few-shot prompting. When the model is not shown any examples, this is called zero-shot prompting. Shots should be of the highest quality

Context 

Here we include any additional context or information that can help the model produce better answers

Question 

This is where we ask the model the question we want an answer for

Model hyperparameters

  • LLM outputs are affected by the configuration hyperparameters of the model, which control different aspects such as how “random” it is.

  • Modifying these parameters allows you to shape the output, making it more imaginative, varied, and engaging, as they influence different aspects of the model's behaviour, including its "randomness.


Temperature: a measure of how frequently the model outputs a less likely word. A higher temperature will produce more creative outputs, and a lower temperature more conservative output. It controls the randomness of the model output

Top p: controls the randomness of the model output using a different mechanism. It sets a threshold probability and selects the top tokens whose cumulative probability exceeds the threshold. The model then randomly samples from this set of tokens to generate output. 

Image prompts

A good prompt can contain the following elements. Not all appear in every prompt but if they do, it is not important that they follow a specific order

Subject 

If your desired image contains one or more subjects, describe with as much detail as possible

Medium 

Add detail on the medium the image you would like

Style 

Describe the style you would like in your image. 

Artist 

You can mention an artist you would like your image to follow the traits 

Website

For niche images there are specialised websites one can include in the prompt. But prompts need to be consistent

Resolution

You can further refine the style with keywords related to resolution

Colour

You can further refine the colour scheme of the image with keywords related to colour

Additional details

Additional descriptive attributes you would like your image to be

BEST PRACTICES FOR PROMPTING

Start simple and iterate adding more elements and context. Try multiple formulations until you find what works best for your task

Be detailed: the more descriptive and detailed your descriptions are, the better results. Use evocative language

Frame from the positive: avoid saying what not to do and say what to do instead

Be consistent: keywords need to make a coherent matching in the prompt

Be specific: include explicits about desired response. Include descriptors to tone or refine the output

Use artist styles sparingly: they have a strong effect. Only choose a given artist if it can give a certain flavour to the image you are after

BE PLAYFUL AND TRY AS MANY OPTIONS AS POSSIBLE. 

THEN ITERATE FROM WHAT WORKS BEST



6. TOWARDS THE FUTURE BIOTECH NANOTECH AND CLIMATETECH


Biotechnology, nanotechnology, and climate tech are broad disciplines considered deep technologies, which are rooted in the advances of cutting edge science and technology. These areas of research and innovation are currently instrumental to address fundamental challenges in society such as climate change, sustainable energy and health as they have the power to change people’s lives and accelerate the green and digital transition

BIOTECHNOLOGY

  • the discipline that uses advances in molecular biology for applications in human and animal health, agriculture, environment, and specialty biochemical manufacturing

  • A technology that utilises biological systems, living organisms or parts of this to develop or create various products

  • In the next century, the major driving force for biotechnology will be the strategic use of genomic information and the power of synthetic biology to use and manipulate life processes in research, medicine, agriculture, and manufacturing

  • A more recent multidisciplinary and data-intensive approach to biotechnology is shifting the pace at which developments occur and our ability to manipulate living matter and organisms


Some of the most relevant technical capabilities in modern biotechnology

  1. Molecular and nano-scale capabilities

  2. Genetic engineering and gene editing

  3. Big biodata and IoT

  4. Biological and non-biological combinations


Key concepts in biotechnology

  • The most basic physical and hereditary unit is the GENE. The DNAstructure consists of 4 different nucleotides in its 3D structure

  • It is the foundation for understanding the genetic code and the basic language of life. This applies to all organisms, from bacteria, plants to animal cells.

  • Genes encode proteins that allow organisms to execute certain functions


Central dogma and the genetic code

The central dogma states that genetic information flows only in one direction, from DNA, to RNA to protein

GENETIC ENGINEERING AS A PIVOTAL TECHNOLOGY IN BIOTECH

  • Genetic engineering is the process that uses laboratory-based technologies to modify the DNA makeup of an organism. This may involve changing a single base pair, deleting a region or adding a new segment of DNA. it comprises multiple techniques for the intentional manipulation of both DNA and RNA to alter, repair or enhance form or function

  • Biotechnology is a rapidly evolving field, especially in the last decade with the advent of gene editing technologies and rapid and powerful sequencing and analytical technologies that allow interrogating genomic information from numerous genomes, regardless of the complexity.

  • Genetic engineering comprises multiple techniques for the intentional manipulation of genetic material (primarily DNA but also RNA) to alter, repair, or enhance form or function

  • recent years, these traditional tools have been supplemented by new techniques to design and build novel life forms,referred to as synthetic biology


  1. DNA synthesis

  2. Cloning of sequence / gene

  3. Plasmid transformation

  4. Cell planting and colony selection

  5. Cell growth and protein extraction

  6. Protein purification

Top biotechnology applications

  • These bio-based technologies have the potential to help meet a rapidly growing demand for energy, food, nutrition, and health and are continually evolving, driven by advancements in scientific understanding, technological capabilities, and the quest for innovative solutions to pressing global challenges

  • For this course's purpose, we will highlight the most relevant applications nowadays and emerging applications that will be possible as technological capabilities fully develop

CRISPR technology

Crispr / Cas9 is a technology that revolutionises gene editing as CRISPR-Cas9 could be programmed with a synthetic guide RNA to cut and edit genomic DNA at the desired location. Currently, CRISPR using Cas13 allows RNA editing. Other techniques include CRISPR base editing and prime editing

Genomic (BIG) data and computational biology

A recent multidisciplinary and data-intensive approach enabled by digital technologies and bioinformatics is enhancing and speeding our ability to manipulate living matter and organisms


A field of bioinformatics and computational biology propelled by AI and big data allows us to study, curate and treat genetic data as computational code. This growth is matched by the weight of these fields as trends in biotech

1. Precision medicine

  • Focuses on tailoring medical treatments to individual patients based on their genetic makeup, lifestyle and environmental factors

  • Drivers of medicine include: cheaper DNA sequencing costs, improved manufacturing capabilities for biopharmaceuticals, gene therapies and increased adoption and accuracy of molecular/genomic diagnostics

  • Gene therapy offers great hope for the treatment of genetic diseases/disorders

  • By replacing the genetic mutation with a “correct version” of the gene, this technology offers a potentially permanent cure.

  • The Ability to restore gene function through cell therapy has transformed medicine such that we may now be ata turning point in our ability to treat diseases with a precise approach

2. Digital healthcare:

This big data combines health, behavioural and personal data that with powerful analytics solutions can be used to radically improve wellbeing activities, prediction of new diseases, prevention treatments and treatment outcomes.

3. Synthetic biology

Synthetic biology is used for sustainable production of bioenergy, materials, drugs and food and for reducing emissions

4. Bioprinting and tissue engineering

  • Cellular and genetic engineering allow the printing of tissues and the creation of genetically tailored animals to produce human organs compatible for human transplantation.

  • Certain chronic diseases, such as diabetes, that require lifelong treatment can benefit from replacing missing or disease organs and tissues


Tech approaches for tissue engineering

  • Undifferentiated cells from skin to develop different cell types for regenerative medicine

  • Cells from animals to regrow in laboratories in food tech

  • 3D bioprinting

  • Implantation of engineered tissue

5. Ecological engineering

  • Agrotechnology can enable new engineered ecosystems of complex organisms to optimise production of food, materials, decontamination and pollution prevention and the use of energy in ways that are more sustainable and efficient

  • Genetically engineered air-filtering plants for indoor pollution: a resistant pothos engineered to metabolise indoor air pollutants, such as the volatile organic compounds (VOCs) produced by paint, gas stoves, and building materials

  • Two symbiotic bacteria are also present in the soil to turn pollutants, such as benzene, toluene and xylene, into sugar and amino acids


Technology based on genetic engineering and microbiology

Neo Plants produce additional enzymes that can use VOCs by using synthetic metabolic pathways inserted in their genomes. They used VOCs as carbon sources in its normal cellular metabolism, in the same way it typically uses CO2, turning the chemicals in plant matter

6. Computer-human interfaces

  • The combination of biotechnology with cognitive sciences, advance materials and artificial intelligence provide the basis for technologies and devices that allow fully integrating machine and human capabilities

  • These technologies include noninvasive or virtual augmentation of physical, visual, tactile, and auditory senses through gloves, glasses, and headsets common in gaming and learning

7. Computational biology and DNA based data storage

  • The vast amount of data in biotechnology required bioinformatics efforts and tech developments from computer science, mathematics, and statistics to be able to manipulate, curate, and analyse the biological data.

  • Computational biology is now a discipline necessary in practically every biotech field, especially if genomic and proteomic data is handled

7. Industrial biomanufacturing

  • The industrial biotechnology employs biological systems and processes to produce a wide range of chemicals, biomaterials, food, therapies and biofuels

  • Advances in plant and microbial synthetic biotechniques should improve precision and efficacy of genetic engineering for sustainability of plant feedstock biomass while decreasing inputs, allowing the production of various bioproducts.

  • Automation and data-driven processes are predicted to improve efficiency, scalability and reproducibility for achieving appropriate quality control of biotechnology products

NANOTECHNOLOGY

Definition 

The technology that allows the manipulation of matter on a near-atomic scale to produce new structures, materials and devices

Nanoparticles 

Particles of a size of just a fraction of the average diameter of a single human hair, measuring just 1 to 100 nanometers

  • Since the late 2010s, nanotechnology has rapidly progressed, with advancements in nanomaterials, nanofabrication techniques and nanoscale characterization tools

  • It has found applications in diverse fields such as electronics, medicine, energy and environmental science

Nanomaterials

  • These have been shown to be lighter, stronger, more durable, and more reactive, with enhanced electrical conductivity and complex architectures, making them suitable for multiple applications, especially for electronics, energy, biomedicine, the environment, and food


Nanomaterials can be broadly characterised into four types: 

  1. Inorganic based nanomaterials 

  2. Carbon-based nanomaterials

  3. Organic based nanomaterials

  4. Composite based nanomaterials

Nanosensors and nanodevices

nanosensors

Tiny devices designed to measure physical, chemical, biological, or environmental information at the nanoscale level and transfer it into data for analysis. They are made from nanomaterials and have unique properties such as a high surface to volume ratio which make them ideal for sensing applications

nanodevices

nanodevices have at least one overall dimension in the nanoscale, or comprising one or more nanoscale components essential to its operation, nanosensors can be reduced in size to the nanoscale, but they could be larger devices that make use of the unique properties of nanomaterials to detect and measure events at the nanoscale

Safety concerns for nanomaterials and nanodevices

  • The pace at which nanotechnology has evolved in the last decades has moved faster than regulatory bodies

  • Given the relative newness of the sector, regulations surrounding nanotechnology are still in development

  • This affects research itself but also policymaking specific to each field of application of nanotechnology

Nanomanufacturing 

The process of manufacturing at the nanoscale and involves a scaled-up, reliable, and cost-effective manufacturing of nanoscale materials, structures, devices and systems

Applications of nanotechnology

Nanotechnology is improving and even changing the paradigm for many technology and industry sectors, including electronics and computing, homeland security, medicine, transportation, energy,food safety, and chemical industry

Nanomaterials for industrial uses

Advances in nanomaterials have opened up new possibilities in various industries. With the use of nanoparticles, 3D Printing and 4D Self-assembling printing are accelerating materialscience. Nanoparticles, CNTs, and nanocomposites are being developed with enhanced properties, including stronger materials

Nanotech for electronics and photonics

Nanoscale materials are used in many IT and electronic applications due to their electrical and optical properties. They enabled smaller, faster, portable and more efficient electronic devices, needed for nanoelectronics

Nanomedicine - biomedicine and healthcare

Nanotechnology enables targeted drug delivery systems, improved imaging techniques, and sensitive diagnostic tools. Nanoparticles and nanodevices are being designed to specifically target disease cells or deliver drugs with greater precision and efficacy, specifically reaching tissues, cells and even inside the cellular nucleus

Nanostructures - energy

Nanotechnology is being explored for energy-related applications, including solar cells,energy storage devices (batteries and supercapacitors), and fuel cells (batteries running on hydrogen and oxygen). use of nanoscale materials and devices to reduce energy consumption, environmental toxicity burdens, and develop clean, affordable energy

CLIMATE TECHNOLOGIES

  • The application of technology and innovation to mitigate and adapt to the challenges posed by climate change

  • This array of technologies is designed to have a minimal negative impact on the environment and address the environmental effects of climate change while conserving resources, promoting renewable energy and reducing greenhouse gas emissions

  • Clean technologies are designed to promote sustainability, improve energy efficiency and mitigate environmental pollution. 

A global priority to reach net zero emissions

The Paris Agreement, a landmark international treaty adopted in 2015, played a significant role in accelerating global efforts to combat climate change and sparked increased interest in climate tech. The agreement's goal to pursue efforts to limit the temperature increase to 1.5degrees Celsius created a sense of urgency and reinforced the need for transformative actions


Four technology value chains contribute about half of the cumulative CO2 savings

  1. Technologies to widely electrify end use sectors

  2. Carbon capture, utilisation and storage

  3. Hydrogen and hydrogen-related fuels

  4. bioenergy

Climate technologies

  • The emergence of climate tech has been driven by technological advancements in renewable energy technologies, energy storage systems, policy frameworks, and the growing awareness of the need for sustainable practices across industries

  • Environmental monitoring using advanced sensors, monitoring systems and data analytics to assess and manage environmental impacts enable real-time monitoring of air and water quality, climate patterns, and ecosystem health, supporting evidence-based decision-making and environmental management

  • Climate tech are focused on building resilience and adapting to the impacts of climate change, such as flood management, drought-resistant crops, climate-smart infrastructure and early warning systems for extreme weather events

  • Investments and collaborations in climate tech are increasing, and the field is attracting innovators, entrepreneurs, and researchers who are dedicated to developing sustainable and low-carbon technologies 

Technologies to tackle a global concern

  • The priorities for achieving a meaningful effect in climate change at a global level point toward renewable energy infrastructure development and power generation, storage and efficiency

  • Advancements in electric vehicles and charging solutions will help enable the transition to zero-emissions transportation by solving infrastructure-related challenges 

Renewables 

Including solar, wind, hydropower, biofuels, among others, are at the centre of the transition to less carbon-intensive and more sustainable energy systems. Advances in renewable energy technologies, including improved efficiency and cost-effectiveness, have led to increased deployment and integration into the energy mix

Bioenergy 

renewable energy derived from biomass,which is organic material that contains carbon absorbed by plants. When this biomass is used to produce energy, the carbon is released during combustion into the atmosphere

Low emission fuels

They comprise liquid and gaseous biofuels, hydrogen and hydrogen-derived fuels, which play an important role in decarbonising parts of the energy system. The most common way to produce green hydrogen is through electrolysis, a process where you split H2O into hydrogen and oxygen by using electricity

Green, blue and grey hydrogen

Today’s hydrogen mostly comes from reacting natural gas with steam, a process known as steam methane reforming, which is highly polluting.

Carbon capture

Carbon capture, utilisation and storage (CCUS) technologies capture carbon dioxide (CO2)emissions from power plants and industrial processes that use fossil fuel or biomass as fuel.CCUS is considered a crucial technology for reducing greenhouse gas emissions and combat climate change

Sustainable agriculture and farming

Sustainable agriculture aims to reduce the environmental impact of farming practices. This includes precision agriculture techniques, smart irrigation farming systems, organic farming methods, regenerative farming, and innovative approaches for crop/livestock protection and nutrient management, such as sustainable fertilisers, advanced sensors and data analytics to optimise resource use, reduce waste, and enhance productivity

Agriculture connectivity

digitised farms will depend on digital and sensor technologies to obtain massive amounts of data.

Sustainable food and farming

Innovation in sustainable food production could help feed a growing global population and protect the planet. Agriculture needs to develop sustainable ways to feed more people while decreasing emissions and becoming more resistant to climate change.

Energy storage

Energy storage technologies are vital to balance the intermittent nature of renewable energy sources. This includes technologies such as advanced batteries, pumped hydro storage, compressed air energy storage, and thermal energy storage. Advancements in battery tech, such as lithium-ion, are enabling the storage of excess renewable energy for use during periods of high demand or when renewable sources are not available

A community based DER technology for NYC

Urban Energy has developed a distributed generation by using rooftops or solar gardens in NYC. By owning and aggregating DERtechnologies they can compete with wholesale electric markets using Virtual Power Plants(VPP) to maximise asset value.The system integrates multiple technologies such as battery storage, EV charging, and air source heat pumps.

Electric mobility

Clean technologies in transportation and energy storage include EVs and associated charging infrastructure. EVs produce lower emissions compared to traditional internal combustion engine vehicles, representing the key technology to decarbonise road transport

Swappable batteries on the road

A new tech to swap electric battery components for EVs. By changing only a few pieces, they increase the battery life and provide a faster system for EVsusers on the road

Waste management

Technologies for innovative waste management and recycling solutions aim to reduce waste generation, promote recycling and reuse, and minimise the environmental impact of waste disposal. Sustainable water management also represents a priority in climate tech with technologies for water purification, desalination, wastewater treatment, and water recycling,promoting water conservation and reducing pollution.

Containers biodegradable out of fungi

A company is developing biodegradable materials grown from mycelium to displace plastic from industries. Mycelium is the vegetative, root-like structure of fungi. The most mature product is packaging, and they have already partnered with large global companies


7. INTERNET AND THE DATA ECONOMY SURVEILLANCE PRIVACY AND REGULATION


THE ORIGIN OF INTERNET

Early visionary in 1962

In the early 1960s, a visionary named J.C.R. Licklider dared to dream of a future where computers could communicate with each other on a global scale. He conceived of a"Galactic Network'' that would connect computers worldwide, facilitating collaboration and resource sharing

The arpanet first step

Lickliter’s vision caught the attention of the Advanced Research Projects Agency (ARPA),a branch of the U.S. Department of Defense. In 1969, ARPA funded the creation of theARPANET, a groundbreaking network that would lay the foundation for the internet as we know it. With its humble beginnings, the ARPANET aimed to connect four major research institutions. It began as a small network, but it held immense potential 

The 70s: email and TCP/IP protocol

As the 1970s dawned, the power of the ARPANET became increasingly evident. In 1971,a young computer engineer named Ray Tomlinson developed a program that would forever change the way we communicate: email. This innovative breakthrough allowedusers to send messages between computers, opening new avenues for information exchange

The 80s: DNS and the birth of the internet

1980, the first TCP/IP specification was published, laying out the rules and protocols that would become the bedrock of the internet. As the ARPANET migrated to the TCP/IPstandard in 1983, a crucial milestone was reached. The internet, in its early form, was taking shape

The 90s: the world wide web was born

in 1990, a brilliant computer scientist named Tim Berners-Lee introduced an extraordinary concept: the World Wide We

HOW INTERNET WORKS

Protocols of 1995 - 2000

During the late 1990s, as indicated earlier, the internet relied on protocols like HTTP, TCP/IP and HTML. these protocols formed the backbone of the world wide web, allowing users to browse websites, send emails and access online services

Rise of big corporations

During the evolution of the internet, not only Meta (formerly Facebook) and Google but also other big corporations like Twitter, Amazon, Spotify... rose to prominence,significantly shaping the online landscape. 

Centralisation and corporate influence

As Meta, Google, Twitter, Amazon, Spotify and other corporations gained power and influence, concerns regarding centralization and corporate control over the internet became more prominent. These platforms served as gatekeepers to vast amounts ofuser data and wielded significant control over content distribution and user experiences

DATA ECONOMY: INTRODUCTION AND IMPORTANCE

It involves the collection and generation of data from various sources, the analysis of that data to derive insights, and the monetization of data through various business models and strategies. Data economy refers to the economic activities and value creation that revolve around the collection, analysis and utilisation of data

Insights and decision-making

Customer preferences. Identify emerging market trends. Better informed business decisions. Data provides businesses with valuable insights into consumer behaviour, market trends and operational efficiency

Personalisation and customer experience

Personalised experiences. Targeted advertising. Customised recommendations. Data allows businesses to personalise their products, services and marketing efforts

Operational efficiency and cost savings

Identify bottlenecks. Streamline processes. Enhance productivity. Data analysis helps businesses optimise their operations and improve efficiency 

Innovation and product development

Stay ahead of the competition. Foster continuous improvement. Data plays a crucial role in driving innovation and product development

Key drivers of the data economy include

Data generation

The creation of data from various sources. These can range from traditional business operations to social media interaction, IoT and more. From various sources, includes structured data as well as unstructured data and the growth of the data economy relies on the continuous generation of data

Data collection

This involves gathering data from various sources for further use. Companies often collect data through direct customer interactions, digital platforms, third party data brokers, or publicly available data. Gathering and acquiring data from different sources, provides the raw material for analysis and subsequent monetisation and data collection methods can vary depending on the type of data and the intended use

Data analysis

Data is raw and unstructured, but through data analysis, businesses can extract meaningful insights. This process involves cleaning, transforming, and modelling data to discover useful information, inform conclusions and support decision making. Extracting insights, patterns and trends from the collected data, various techniques and technologies are used for data analysis and the goal is to derive actionable insights and knowledge 

Data monetization 

The methods used by companies to turn collected and analysed data into economic value or revenue. Monetization can occur directly through selling data or indirectly by improving business operations, creating better products or services, or enhancing customer experiences. Process of deriving value and generating revenue. Organisations can monetize data in different ways and it can also involve data sharing partnerships, data marketplaces and the creation of new business models centred around data

PLAYERS OF THE DATA ECONOMY

Data producers

These are entities that generate data, often as a by-product of their main activities. This can include individuals creating data through their online activities, businesses creating data through their operations, or IoT devices generating data through their sensors. Individuals on-line activities, business operations and IoT sensors

Data consumers

These entities use data to drive their decisions or improve their operations. Data consumers can include businesses, researchers, government agencies or even individuals. They use data to inform decisions, discover insights or build products and services.

Data brokers

These are entities that collect data from various sources, aggregate it, and then sell it to other entities, usually for marketing or research purposes. 

DATA MARKETS VS DATA COMMONS VS DATA TRUSTS

Data markets

Platforms where data is bought and sold. They are often commercial in nature and facilitate transactions between data producers (sellers) and data consumers (buyers)

Data commons

These are shared resources where data is made openly available to anyone. They are based on the principles of open data and are often used for public or communal benefit. It is open data

Data trusts

Legal structures that provide a fiduciary responsibility to look after data on behalf of a group of data subjects. 

THE ROLE OF DATA IN BUSINESS AND REAL WORLD APPLICATIONS

Data plays an integral role in contemporary business operations, significantly contributing to decision making, gaining customer insights and boosting operational efficiency. In this digital age, data driven decisions often make the difference between successful businesses and those that fail. 

Real world examples: 

Amazon: Amazon analyses customers' browsing and purchasing history, along with other data points, to provide personalised product recommendations

Uber: Uber uses data in several ways, including efficient ride allocation and dynamic pricing. It dynamically adjusts its prices to maintain a balance

Netflix: They use data to analyse viewing patterns and habits of their subscribers, which allows them to provide personalised recommendations

Starbucks: Starbucks is a company that uses data to improve its operations and customer service. They have a mobile app that collects data about purchase history,location, and time of order

CONCEPTS OF SURVEILLANCE, PRIVACY AND REGULATION 

Surveillance 

surveillance refers to the monitoring of individuals' activities, behaviours, or communications through data collection

Privacy 

Privacy refers to an individual's right to keep their personal information private and control who has access to it. In the data economy, privacy becomes a major concern because vast amounts of personal data are constantly being collected and traded

Why is data important for companies?

  • Compliance with regulations

  • Trust and reputation: proper data handling builds consumer trust

  • Prevention of financial loss: data breaches can result in significant financial loss due to penalties, loss of customer trust, and remediation costs

  • Competitive advantage: a robust data privacy strategy can act as a differentiator in the market

How can businesses maintain their competitive edge while ensuring robust data privacy policies?

Data minimization: companies should only collect necessary data, reducing the potential harm in case of a data breach

Transparency: companies should be transparent about their data practices

Consent management: companies should obtain consent from individuals before collecting or processing their personal data

Security measures: implementation of appropriate security measures to protect data from unauthorised access, alteration, or deletion is a must

Data lifecycle management: companies should have policies regarding data retention and deletion

Data breach response plan: companies should have a plan to respond quickly to data breaches to minimise damage, including notifying affected individuals and regulatory authorities

Regulation 

Regulation in the data economy involves rules and laws that govern how data is collected, stored, shared, and used. Regulations aim to protect individuals privacy, ensure data security, and prevent misuse of data. Regulations are put in place to strike a balance between enabling the benefits of data collection and use and protecting individuals’ rights to privacy

Data regulations and business strategies

  • Laws that control how business can collect, store, manage and process data

  • They have significant implications for businesses

  • They mandate businesses to maintain high standards of data privacy and security to protect the rights and freedoms of individuals

  • Compliance with these laws often necessitates a change in business strategies

  • These three concepts are interrelated in the data economy

  • The extensive surveillance made possible by modern technologies raises significant privacy concerns, which in turn drives the need for regulation

  • Regulations are put in place to strike a balance between enabling the benefits of data collection and use and protecting individuals’ rights to privacy

  • However, the fast paced evolution of the data economy presents ongoing challenges to ensuring effective regulation

Surveillance: 

  • The surveillance economy describes the business of collecting and monetizing people’s personal information at scale, and the companies that are involved in this business

  • The desire to escape the invasive surveillance of the data economy is a core driver of the global push for greater consumer privacy and control of personally identifiable information

Privacy: 

  • Data privacy, also known as information privacy, is the aspect of data protection that deals with the proper handling of data concerning consent, notice, and regulatory obligations.

  • Involves managing personal information in ways conformable to laws and regulations, including how it is collected, stored, used and deleted

What is data privacy

Data privacy is the aspect of data protection that deals with the proper handling of data concerning consent, notice and regulatory obligations. It involves managing personal information in ways conformable to laws and regulations, including how it is collected, stored, used and deleted. Data privacy is extremely relevant to businesses

Why is data privacy important for companies?

Compliance with regulations

Around the world, regulations such as the general data protection regulation in the EU, California consumer privacy act in the US, or similar laws in other regions mandate strict data privacy standards for businesses. Non compliance can lead to hefty fines, and in severe cases, cessation of operations

Trust and reputation

Proper data handling builds consumer trust. In an era where data breaches are prevalent, companies that respect user privacy and prioritise data protection are viewed more favourably, contributing to a positive brand image

Prevention of financial loss

Data breaches can result in significant financial loss due to penalties, loss of customer trust, and remediation costs. Companies that prioritise data privacy are better prepared against these threats

Competitive advantage

A robust data privacy strategy can acts as a differentiator in the market. Customers increasingly value their privacy and are likely to prefer businesses that respect and protect their personal data

How can businesses maintain their competitive edge while ensuring robust data privacy policies? Here are some areas where companies should excel:

Data minimisation

Companies should only collect necessary data, reducing the potential harm in case of a data breach

transparency

Companies should be transparent about their data practices. This includes clear communication about what data is being collected, why its collected, how it is used and who it is shared with

Consent management

Companies should obtain consent from individuals before collecting or processing their personal data

Security measures

Implementation of appropriate security measures to protect data from unauthorised access, alteration or deletion is a must. These include, encryption, regular patching, secure user authentication and regular security audits

Data lifecycle management

Companies should have policies regarding data retention and deletion. Personal data should be securely deleted when no longer necessary

Data breach response plan

Companies should have a plan to respond quickly to data breaches to minimise damage, including notifying affected individuals and regulatory authorities

Data privacy is a business necessity in the digital age. It should not be viewed as a mere compliance exercise but as a commitment to customer welfare, ethical business practices and long term business sustainability

Regulation 


Data regulations and business strategies

  • Data regulations are laws that control how businesses can collect, store, manage and process data.

  • They have significant implications for businesses

  • First, they mandate businesses to maintain high standards of data privacy and security to protect the rights and freedoms of individuals. 

  • The general data protection regulation (GDPR) in the EU and the California consumer privacy act (CCPA) in the US are prime examples of such laws

  • Compliance with these laws often necessitates a change in business strategies. It Could mean designing systems with privacy in mind from the outset or implementing stricter data access controls

  • It could also involve increased transparency about data usage with clients and customers, which can foster trust and improve customer relations


The 2017 Equifax breach: a cautionary tale

  • Equifax, a credit reporting agency, suffered a massive cyber-attack that exposed the sensitive personal information of 147 million people

  • The breach was due to its failure to patch a known vulnerability in their system, demonstrating a lack of adequate data security measures

  • The equifax case clearly illustrates the potential repercussions of non-compliance with data regulations and lax data security

  • It underscores the reality that the cost of preventive measures is often far less than the cost of dealing with a breach

  • Therefore, businesses must not only comply with data regulations but also go beyond minimum requirements to ensure robust data security


Penalties for non compliance

  • Non-compliance with data regulations can lead to severe penalties

  • Depending on the law and the severity of the infraction, these penalties can range from significant fines to lawsuits and even prison terms

  • Breaches can also damage a company’s reputation, affecting customer trust and long-term profitability

  • Therefore, avoiding these penalties is a key motivator in the drive towards data regulation compliance

THE IMPORTANCE OF UNDERSTANDING REGIONAL DIFFERENCES

  • The regulatory landscape for privacy laws varies widely, particularly in different regions, such as Europe and the United states. 

  • It is essential to understand these differences and the implications they have on global business and individual privacy rights

  • As we move towards an increasingly interconnected world, it is crucial to keep these geographical differences in mind and to anticipate potential changes in the global privacy law landscape

  • It is not just about adhering to regulations - it is about recognizing the value of privacy and using it as a competitive advantage


8. CYBERSECURITY


INTRODUCTION

In today's interconnected world, where technology permeates every aspect of our lives, it is crucial to understand the importance of cybersecurity

cybersecurity

The practice of protecting computer systems, networks and data from unauthorised access, damage or theft. It encompasses a wide range of measures and strategies designed to safeguard information and preserve the integrity of digital systems

  • While the increasing reliance on technology for communication, commerce, education and entertainment, the risk of cyber threats and attacks has also grown exponentially

  • Cybercriminals pose a significant threat to individuals, organisations and even for nations

  • Personal information, financial data, intellectual property and sensitive government documents are all potential targets

  • Cyber Attacks can result in financial loss, reputational damage, disruption of services, and even compromise national security

  • It is therefore, imperative for individuals to understand the fundamentals of cybersecurity to protect themselves and contribute to a safer digital environment

  • Cybersecurity is organised under the CIA triad: confidentiality, integrity and availability 

Confidentiality 

Ensuring that sensitive information remains private and accessible only to authorised individuals

Integrity 

Maintaining the accuracy and trustworthiness of data, preventing unauthorised modifications or tampering

Availability 

The uninterrupted access and functionality of systems and networks

  • To achieve these objectives, cybersecurity employs various techniques and practices such as encryption, firewalls, intrusion detection systems and antivirus software

Encryption 

Scrambles data to make it unreadable to unauthorised users. It is the conversion of electronic data into a form called ciphertext using keys

Firewalls 

Monitor and control network traffic. The first line of defence in a network connected to the internet. They control the flow of information to all the devices attached to their network, filtering both incoming and outgoing traffic

Intrusion detection systems

Identify and respond to malicious activities

Antivirus software

Detects and removes malware

CYBERSECURITY CONCEPTS

Vulnerability 

A weakness in a system or its design that can be exploited by a Threat

Threat 

An external menace to that system

Threat agent 

The entity that identifies a Vulnerability and uses it to attack the victim.

Risk 

the likelihood that a particular threat, using a specific attack, exploits a particular vulnerability of a system, which results in an undesirable consequence (Incident).

Exploit 

A sw tool developed to take advantage of a Vulnerability

Exposure 

The potential to experience losses from a Threat Agent

Countermeasures 

The techniques or methods used to defend against attacks and to solve or compensate Vulnerabilities in networks or systems

Cost 

Security is always a compromise between the cost of protecting assets and the cost of those assets being breached

Confidentiality 

Preserving authorised restrictions on information access and disclosure, including means for protecting personal data and proprietary information.

Integrity 

Guarding against information modifications or destruction, including ensuring information non-repudiation and authenticity

Availability 

Ensuring timely and reliable access and use of information

Authenticity 

Verifying that users are who they say they are and that each input arriving at the system came from a trusted source.

Accountability 

The security goal that generates the requirement for actions of an entity to be traced uniquely to that entity.

Phishing 

Social engineering technique that attempts to acquire sensitive information, usually login credentials or credit card data, by masquerading as a trustworthy organisation

Malware 

The term used for all these types of software:

Viruses 

Destructive programs designed to replicate and spread on their own. Many types: trojans, worms and rootkits

Ransomware 

Software designed to keep the user from their data and hold it hostage for payment

Spyware 

Programs are generally introduced to the system through Internet Downloads that appear to be useful programs. Once spyware is installed on a system, it monitors the system’s operation and collects information such as usernames, passwords, credit card numbers, and other PII. software that collects personal information from host where it is installed

Adware 

Introduce unwanted, unsolicited advertising displays to web browsers. They can also be designed to gather user selection information from thebrowser, constructing a more personalised advertising scheme. 

Logic bombs

Type of malware typically used to delete data when a specific logical event is concluded

Zombies 

Infected computers that can be placed under the remote control of a malicious user. 

Botnets 

A large collection of zombies, or bots, controlled by a bot herder. This Type of network can consist of literally millions of unsuspecting computers.

Man in the middle attack

It is a cyberattack where the attacker secretly relays andpossibly alters the communications between two parties who believe that they are directly communicating with each other, as the attacker has inserted themselves between the two parties

Firewall 

Firewalls are the first line of defence in a network connected to the Internet And they control the flow of information to all the devices attached to their network,filtering both incoming and outgoing traffic

VPN

A virtual private network (VPN) is a mechanism for creating a secure connection between a computing device and a computer network, or between two networks, using an insecure communication medium such as the public Internet

Cryptography 

the concepts and methods for securing information.

keys

A data string used to encrypt or decrypt information

Encryption keys

Based on a “secret” string that is known only to the software that encrypts and decrypts the data or it may be randomly generated

cipher

The algorithm that performs this encryption or decryption

Scrambled message

Produced by the cipher and it cannot be understood without the knowledge of the cipher that was used to create it

Symmetric key

If the same key is used for both encryption and decryption

Asymmetric keys

If a different key is used for encryption than decryption

Digital certificates

Digital verifications that the sender of an encrypted message is who they claim to be

CYBERSECURITY STAKEHOLDERS

In the field of cybersecurity, there are several key stakeholders who play important roles in ensuring the security and protection of digital systems, networks and data. The main stakeholders in cybersecurity are:

Individuals 

One of the primary stakeholders in cybersecurity. They include end-users, employees and consumers who use various digital technologies and interact with online platforms

Organizations 

Including businesses, government agencies, educational institutions, and non-profit organisations, are significant stakeholders in cybersecurity. They have a responsibility to protect their own digital assets, sensitive data and the privacy of their stakeholders

Governments 

They are responsible for formulating policies, regulations and legislation related to cybersecurity. They establish cybersecurity frameworks, promote information sharing and enforce laws to protect critical infrastructure and combat cybercrime

Cybersecurity professionals 

Including security analysts, engineers, consultants and researchers, are essential stakeholders in safeguarding digital systems. They specialise in identifying vulnerabilities, implementing security measures, conducting risk assessments, responding to incidents and developing strategies to mitigate cyber threats

Technology providers

Including hardware and software vendors. They develop and deliver products and services that incorporate security features and help protect against potential threats

Regulatory bodies and standards organisations

Establish guidelines and frameworks to promote cybersecurity best practices. They develop industry standards, certifications and compliance requirements that organisations must adhere to 

Law enforcement and intelligence agencies

These play a critical role in investigating and combating cybercrime. They collaborate with other stakeholders, monitor cyber threats, gather intelligence and enforce laws to identify and prosecute cybercriminals

HOW CAN TECHNOLOGY HELP ACHIEVE CYBERSECURITY

  • Technology plays a crucial role in achieving cybersecurity by providing the necessary tools, solutions and frameworks to defend against evolving cyber threats.

  • With the rapid advancement of technology, cybersecurity has become increasingly complex, requiring robust measures to safeguard digital assets and sensitive information

  • One of the key ways technology helps achieve cybersecurity is through the development and deployment of advanced security systems and software

  • Technology enables continuous monitoring and real-time analysis of network traffic and user behaviour, allowing for the prompt detection and response to cyber incidents

  • Technology facilitates the implementation of secure coding practices and secure software development lifecycles

ATTACK TARGETS

Physical equipment

Stealth, destruction, accidents, misuse

Resource utilisation

Availability, economic loss, performance (speed, storage, bandwidth …)

Stored information

Modification, fabrication, destruction, leaks

On-transit information

Interruption, interception, modification, fabrication

Public image and reputation

Disclosure of private information, negative publicity, exposure of inability to secure information