MIS560

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53 Terms

1
reactive machines AI
basic operations; simplest, no learning
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limited memory AI
predictive; store previous data to make bettter predictions
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theory of mind AI
interact with thoughts of humans; do not exist yet, are in development
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self-ware AI
evolved to be akin to the human brain that it has self-awareness (has it’s own emotions & understand emotions)
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supervised
trained with given sample data with a known output
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unsupervised
trained with given sample data without a known output
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semi-supervised
combination of supervised and unsupervised learning
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reinforcement
trained by trial and error; program explores their environment and receives or negative rewards based on actions
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Types of supervised ML algorithms
linear regression, logistic regression, & Naive Bayes classifier
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Deep Learning
based on learning examples (like humans) using artificial neural network; mimics neurons in the human brain
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types of unsupervised ML algorithms
K means clustering, apriori
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12
Deepfakes
use of AI and ML to create lifelike but fake images of real people, AI is fed images of the person to replicate, even voices
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Ethics of Deepfakes
misinformation, cyberbullying, dead actors & influencers, laws
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14
In functional programming, was is data center around?
functions
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What kind of programming are we most familar with?
Imperative & OOP programmin
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What are some benefits or functional programming?
concurrency, fault tolerance, easier to debug, shorter code, more math-based
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Lewin’s 4 Golden Rules of Changes

1. change should only be implemented for good reason, 2. change is most effective when done gradually 3. change should be planned and not sporadic or sudden, 4. strive to include individuals who may be affected by the change as much as possible in planning for the change
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3 Stage model
unfreeze(ensure ready for change), change (execute the intended change), refreeze (change becomes permanent)
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Things that can help change
help people understand what’s in it for them, some people may be harmed by the change: this is important to actively manage
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Critiques of the model
it is quaint & simple for the modern era, linear in nature when projects and change are often not, little to no emphasis on people’s emotional journey
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ethics are involved at multiple levels
individual, community, business, government, society
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what is ethics?
refer to standards and practices that tell us how humans ought to act in multiple situations and different roles
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What is ethics NOT?
feelings, religion, law, accepted norms, science
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What are the 6 ethic lenses?
rights, common good, utilitarian, virtue, care ethics, justice
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The rights lens
ethical action is the one that best protects and respects the moral rights of those affected; dignity based on human nature, choose freely to live their own lives
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The justice lens
each person should be given their due, and what people are due are often interpreted as fair or equal treatment; people are treated as equals but not necessarily the same
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different types of justice
social, corrective, retributive, restorative, distributive
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The utilitarian lens
ethical action is the one that produces the greatest balance of good over harm for the most stakeholders; the greater good
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the common good lens
interlocking relationship of society are the basis of ethical reasoning; respect and compassion for all others are requirements of such reasoning; life in community is a good itself
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The virtue lens
ethical actions ought to be consistent with certain ideal that provide for full development of humanity; ancient approach
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Virtues are dispositions and habits that enable us to act according to the highest potential of our character. These include:
honesty/integrity, courage/fidelity, compassion/generosity, tolerance/fairness, love/self-control
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The care ethic lens
is rooted in relationships and in the need to listen and respond to individuals in their specific circumstances; not merely following rules or calculating utility; connects interpersonal duties to social duties
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Main problems of these lenses:
definition of human & civil rights, definition of what constitutes the common good, definition of what is a good and what is a harm
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What pending question does the different lenses lead to different answers?
What is ethical?
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5 steps within the framework for ethical decision-making
  1. identify the ethical issues

  2. get the facts

  3. evaluate alternative actions

  4. choose an option for action & test it

  5. implement your decision & reflect on the outcome

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What is data analytics?
analyzing raw data to formulate conclusions
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descriptive analytics
what HAS happened
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predictive analytics
what COULD happen
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prescriptive analytics
what SHOULD happen
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diagnostics
WHY did something happen
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Stages of a Process flow
  1. data collection/extraction,

  2. data organization/storage,

  3. data cleaning & transformation,

  4. KPI (Key Performance indicator)/insight derivation

  5. data visualization

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common use cases of D.A.
  1. e-commerce

  2. manufacturing

  3. IT security

  4. healthcare

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Benefits of Data Analytics
  1. performance measurement

    1. social media usage & engagement

    2. summarize effectiveness of marketing campaigns or business operations

    3. interpreting survey results

  2. improvement of business processes

    1. more efficient inventory forecasting

    2. pattern detection to prevent fraudulent activity

    3. risk reduction

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What are some ethical concerns around data analytics?
  1. privacy & security

  2. transparency & accountability

  3. fairness & non-discrimination

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ethical determining questions
  1. is it legal?

  2. is it ethical?

  3. how will our customers react?

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Pros of Proliferation of Data Privacy
  1. stronger consumer protections

  2. more responsible use of data by corporations

  3. improved ability to respond to breaches

  4. stronger requirements to notify of breaches and ability to impose penalties

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Cons of Proliferation of Data Privacy
  1. significant organizational effort to implement

  2. different protections in different states

  3. frequently law makers do not understand all issues involved

  4. largely operates on trust - cannot check that everyone did it correctly

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Ethics of AI examples
  1. biases in systems

  2. liability in failure

  3. profiling & unnecessary intrusion

  4. plagiarism

  5. unnecessary collection

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Problems with monolith
  1. long build/test/release cycles

  2. scalability is compromised

  3. lack of agility

  4. software architecture is hard to maintain and evolve

  5. system operation is difficult

  6. lack of innovation

  7. slow development pace

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Microservices
software architecture style in which complex applications are composed of small, independent processes communication with each other using language-agnostic APIs. (highly decoupled & focuses on smaller tasks)
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Benefits of a microservice architecture
  1. improves fault isolation

  2. eliminates long-term commitment to a single technology stack

  3. improved agility

  4. provides the ability to “fail fast” and recover fast

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What is the trade-off of microservices?
  1. can be complex

    1. some services can be up while others are down

    2. remotes calls experience latency

  2. premium placed on automated deployment

  3. increased security vulnerabilities

  4. more complex data management

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