M3 Technology, Surveillance, and Obtaining Consent

Ethical Dilemma

A situation where conflicting moral principles or values make choosing a clear “right” action difficult

• Examples:

  • Stealing food to feed family: Hunger vs Law

  • Playing through injury or pain

    • Structural issues: Athletes may lose opportunities, scholarships, or face penalties if they don’t play

    • Cultural issues: Hyper-masculine culture in competitive sports often equates playing through pain with strength and masculinity, reinforcing the metaphorical view of the body as a machine

  • Limited Hospital Beds

    • Doctors must decide who receives care when resources are scarce

  • Moving Away for University/Hockey

    • Personal career advancement/enjoyment vs family expectations/worry

  • Transgender athletes inclusion

    • Fairness vs anti-oppression. Anti-oppression lens defends inclusion by focusing on eliminating historical and contemporary oppression against groups like LGBTQ+ individuals

  • Catching a friend engaging in Academic Dishonesty / Organizational Misconduct

    • Loyalty to a friend/employer vs reporting unethical behaviour

Moral Compass

When facing ethical dilemmas, decision-making can be guided by

• Law: Federal, state, local bylaws, policies

• Organizational: UofT guidelines, organizational values

• Professional Ethics: e.g. the Hippocratic Oath for doctors, emphasizing non-refusal of patients regardless of personal values'

• Social Ethics: mutual cooperation, support, loyalty, fidelity, the greater good, family values, the tragedy of the commons illustrates the negative consequences when individual will outweighs social will

• Personal Integrity: Inner harmony, self-respect, dignity, happiness

• Morality: Broader, abstract concepts defined by ethical frameworks such as biomedical ethics or principlism which include:

  • Autonomy

  • Respect

  • Trust

  • Beneficence

  • Non-maleficence

  • Fairness

  • Equity

Reasonable Approach to Ethical Dilemmas

1. Bring all stakeholders together

2. Explain the context of the dilemma (history, elements)

   1. e.g. Toronto’s FIFA World Cup preparations — vendor selection, hiring, economic opportunities vs. negative impacts (traffic, noise, crime)

   2. Stakeholders need assessment

3. Identify values/issues in conflict

4. Clarify and weight the relative importance of conflicts

5. Find options to resolve the dilemma and receive feedback

6. Choose a reasonable, rationalized solution

TDSB Admission

Case where TDSB shifted from lottery system for specialized programs to merit-based admissions

• Weighting: 30% report card achievement, 70% knowledge/skills evaluation

• Arguments for: Removes long-term barriers, rewards hard work, improves access, centralizes applications, favours students with propensity for programs

• Arguments against: Lottery disregards focus/attainment, individual schools must modify pedagogy, may not always solve structural inequities (e.g. wealthier families can better support children with special abilities)

Supreme Court Ruling

R vs. Brown-Solomon

• May 2022 ruling: Extreme intoxication defence could be used for violent crimes, striking down Section 33.1 of the Criminal Code (which disallowed self-induced extreme intoxication defence)

• Parliament’s response (June 2022): Passed BIll C-28, creating a new criminal negligence offence

• Ethical Dilemma: constitutional rights of accused vs protection of vulnerable communities (who are more prone to harm)

• Rationale for ruling: alcohol alone unlikely to cause extreme intoxication; considering other factors and protecting individuals acting out of character

• Moral compass used by Supreme Court: The constitution (supreme law of the land)

Technology Surveillance and Digital Ethics

General Ethical Issues

• Patient/client/student rights

• Ethical responsibility to employees and staff

• Professional codes of ethics

• Violation of policy and practices

• Community values and experiences (e.g. Indigenous and racialized populations’ distrust of healthcare due to historical misconduct)

• Conflict of interest: Professional vs. personal/religious obligations (e.g. working for an alcohol company as a Muslim)

• Professional standards of ethical conduct

Personal Experiences with Surveillance

Class feels they are under surveillance by phones AI (e.g. Gemini), social media, and search engines

• Online ads mirror conversations or even thoughts

• Data filtered by algorithms and sold to marketing groups

• Concerns about group chats being monitored for jokes (e.g. “bomb” joke incident)

• Worry about tracking of personal data, such as women’s menstrual cycle data

• Lack of full understanding where personal info goes, especially with LLMs storing conversations

• Risk of data breaches (e.g. ransomware outbreaks)

  • UofT’s strategy of separating critical info into different divisions/apps mitigate this

Why People Don’t Read Terms and Conditions

1. Too long and complex/wordy

2. Lack of time, energy, or intellectual knowledge to understand what exactly it entails

3. Trust in reserachers or document preparers

4. Oral explanations by others to replace reading

Companies’ ulterior motives: Intentionally make policies complex so people don’t read them, allowing them to sell data or be protected if issues arise

Forced consent: Often no choice but to accept T&C to use essential services (email, social media)

Informed Consent

Critical for medical procedures, health services, reserach studies, and use of personal info/photos

Factors affecting informed consent:

• Readability/Vocabulary: Documents are often too complex

• Age, education, cognitive/mental status of individuals

• Key components of autonomy: Informed consent, freedom from coercion, and cognitive ability

Levels of consent in research: Communal consent (oral) and written

Health Apps and Gadgets

Used to quantify and monitor health (quantified self?)

• Information tracked: steps, heart rate, sleep, weight, menstrual cycle

Technology and Surveillance Discourses

Accountability

• Limited oversight of platforms and software

• Difficulty identifying when info is misused (unless direct impact like credit card fraud)

• Lack of strong consequences / harsher punishments for misuse

Rapid Pace of Development

• Constraints ability to adequately research and analyze ethical considerations (outpacing)

Data Ownership

• Large corporations (Facebook, Google, Apple) own vast amounts of personal data

• Sophisticated methods to collect, sell, and share info w/ third parties without full understanding of consent

Digital Divide

• Unequal access to internet/technology

• Differences in connection quality and network availability (e.g. rural vs urban areas)

Algorithm Oppression

• Lack of digital literacy prevents participation and engagement with online platforms

• Third-party data used in ways not understood by software engineers

• Algorithms can perpetuate existing inequities (e.g. in job applications, facial recognition)

Marginalized Communities and Consent

Increased Risk:

• Still used for high-risk research studies, often w/o adequate info on potential harm, risk, or benefit

Adverse Health Effects:

• May lack knowledge to understand health consequences

History of Transgression:

• Past misuse, exclusion, and negligence by the larger health industry leads to continued distrust (e.g. racialized, Indigenous communities). This results in many not seeking medical attention

Systemic Discrimination:

• Ongoing exclusion (e.g. initial COVID vaccination allocation favoured non-racialized and higher economic classes) further impacts heatlh

Lack of Transparency:

• Reproduces structural inequities among marginalized communities