Ethics 9/12

Context and Lecture Focus

• This lecture is part of a series titled Questions About Part One, following earlier talks on cultural anthropology and issues of cultural relevance.
• Focuses on two areas of recent work and their application to ethics:
  • Evolutionary theory applied to social organization, especially E. O. Wilson’s sociobiology
  • Game theory and its application to social organization, notably John von Neumann (and Morgenstern) and later John Nash
• Central question: Do these theories threaten or illuminate social ethics? They can either help us understand social organization and ethics, or — as E. O. Wilson suggests — threaten ethics by offering an explanation that may undermine the justification for moral beliefs.
• Core issue: Evolutionary ethics may provide an explanation for why we have ethical beliefs, but it might fail to justify those beliefs. This could unglue explanation from justification, posing a potential threat to traditional ethical justification.

Evolutionary Ethics: Threat or Promise to Ethics?

• Traditional aim of theoretical ethics: uncover the underlying structure of moral judgment that justifies a broad range of ethical attitudes. This involves two linked goals:
  • Explanation of why ethical intuitions arise (causal/history-based accounts)
  • Justification of those intuitions (normative grounds for acting morally)
• Evolutionary ethics raises a potential problem: we might obtain an explanation of ethical beliefs that does not justify them. In other words, the two aims (explanation and justification) might diverge.
• Sociobiology (Wilson) and contemporary game theory can be read as posing this kind of threat: they may explain ethical beliefs by evolutionary or strategic considerations but might undercut their justificatory status.

Sociobiology and Altruism: Mechanisms and Tensions

• Sociobiology (E. O. Wilson) explains cooperation and altruism across species, including humans.
• Examples of altruism in nature:
  • Bees sacrifice themselves for the hive
  • Antelope alert others to danger at personal risk
  • Humans often act altruistically, sometimes sacrificing for others
• Evolutionary question: How can cooperation and altruism persist if natural selection favors traits that aid replication of genes?
• Evolutionary explanation: altruism can be favored if it provides evolutionary advantage through relatedness or group benefits. Key mechanisms:
  • Kin selection: sacrificing for close kin can spread the altruist’s genes via relatives
  • Group selection: cooperative groups may be more likely to survive
• Critical caveat: Sociobiology’s explanatory claims are not universally established for all cases of cooperation and altruism; it remains a contention rather than a settled doctrine.

The Threat in a Nutshell: Explanation Without Justification

• If ultimate explanations (genetic advantage, natural selection) account for ethical beliefs, these beliefs might be seen as mere epiphenomena of evolution rather than morally warranted commitments.
• A representative quote reflects this possibility (attributed to Michael Roos in the talk):

Is it not the case that sometimes when one is given a causal explanation of certain beliefs, one can see that the beliefs themselves neither have a foundation nor could ever have such a foundation. Once we see that our moral beliefs are simply an adaptation put in place by natural selection in order to further our reproductive ends, that's an end to Morality is no more than a collective illusion fobbed off on us by our genes for reproductive ends.

Game Theory and Ethics: A Broad View

• Origin: game theory develops from John von Neumann and Oskar Morgenstern (1944), The Theory of Games and Economic Behavior; later key figure John Nash.
• Core idea: different situations (games) involve different strategies; rationality in cooperation and competition is central to understanding social interactions.
• Relevance to ethics: ethical thinking can be reframed as reasoning about strategic interactions among multiple agents, not just a single agent acting in a vacuum.
• Two important features:
  • Social interactions matter: ethics is not just about individual rules but about how individuals interact with others.
  • Focus on two-person games has been dominant due to tractability; multi-person games are more complex mathematically.
• Distinction between zero-sum and non-zero-sum games:
  • Zero-sum: one player’s gain is exactly the other’s loss; total payoff sums to zero
  • Non-zero-sum: both sides can gain, or both can lose; outcomes are not constrained to sum to zero
• Historical context: in the Cold War, the US and USSR faced a non-zero-sum strategic situation in nuclear competition: both sides could lose, making cooperation possible yet fraught with risk.

The Prisoner’s Dilemma: A Canonical Model

• Setup: Lefty and Scarface are arrested for bank robbery; separated so they cannot communicate.
• Payoff story (in years in prison):
  • If both stay mum: each gets 2 years
  • If Lefty stays mum and Scarface confesses: Lefty gets 5 years, Scarface gets 0 years
  • If Lefty confesses and Scarface stays mum: Lefty gets 0 years, Scarface gets 5 years
  • If both confess: each gets 4 years
• Payoff table (in years):
  • 
    egin{array}{c|cc}
    & ext{Scarface: Stay Mum} & ext{Scarface: Confess} \ \
    \hline
    \text{Lefty: Stay Mum} & (2,2) & (5,0) \
    \text{Lefty: Confess} & (0,5) & (4,4) \
    \end{array}
• Basic insight: each prisoner’s best response depends on the other’s action; the dominant strategy is to defect (confess) regardless of the other’s move, leading to a collectively worse outcome (4,4) than mutual cooperation (2,2).
• One-shot vs iterated versions:
  • One-shot: players decide once; defection dominates; mutual defection is the typical equilibrium.
  • Iterated: players interact repeatedly; strategies can evolve over time; cooperation can emerge under certain conditions.

Iterated Prisoner’s Dilemma: Strategies and Dynamics

• Iterated version: two players play again and again (e.g., 20, 200, or an unknown number of rounds).
• Possible strategies in iterated PD:
  • All defect: always defect, regardless of the other’s history
  • All cooperate (quaker or doormat): always cooperate, regardless of the other’s history
  • Tit for tat: start cooperative; then copy the opponent’s previous move (cooperate if they cooperated last round; defect if they defected last round)
• Tit for tat emphasizes reciprocity: cooperation begets cooperation, defection begets defection.

Axelrod Tournaments and Lessons for Cooperation

• 1980 tournament: Robert Axelrod invited strategies from various disciplines; they competed in a round-robin where each strategy played every other strategy, including itself.
• Results: Tit for tat emerged as the winner of the 1980 tournament due to its robustness and simplicity.
• 1981 tournament: Axelrod organized a second tournament, this time with the knowledge that tit for tat had won the first round; strategies that could beat tit for tat were submitted and competed.
• Result: Tit for tat won again in the 1981 tournament, showing its resilience even when it faced strategies designed to counter it.
• 1981 expansion: Axelrod and William Hamilton introduced an evolutionary twist: strategies could be propagated through a population. More successful strategies would constitute a larger share of the population over time.
  • In this evolutionary-iteration framework, strategies that perform better in the population dynamics tend to proliferate; less successful strategies die out over time.

Key Implications of the Tit-for-Tat Result

• Two important points:
  • Tit-for-tat’s success is not because it rewards ethical behavior per se; it accrues because it earns more points (better outcomes) overall against a broad variety of strategies in the tournament and population dynamics.
  • Despite its success, tit-for-tat aligns with ethical intuition in a familiar way: it mirrors the Golden Rule by responding to others’ actions with analogous actions (cooperation or defection).
• The Golden Rule origin and relevance:
  • One of the first documented formulations exists in ancient Egypt and appears in Zoroastrian texts, phrased as acting toward others in the way you would want them to act toward you.

Can Evolutionary or Game-Theoretic Views Undermine Ethics?

• The talk argues that even though sociobiology and game theory offer powerful explanations for cooperative behavior, they do not by themselves undercut ethical intuitions.
• Instead of erasing moral value, these theories may reframe ethical reasoning as grounded in evolved emotional and cognitive resources (sympathy, concern for others, reciprocal expectations) that guide cooperative behavior.
• Evolutionary explanations may illuminate the origins of ethical feelings but cannot, by themselves, determine how we ought to act in any given situation.
• The author emphasizes: People have choices and exercise agency; different individuals can act for self-benefit or for others, and even the same person may act differently in different circumstances.
• The philosopher Philip Kitcher is cited to argue that genetic makeup explains the origins of certain cognitive tools but does not explain the content of our choices; evolution explains the ability to reason, not the content of the output of reasoning.
• Analogy to color vision: evolution explains why we can see colors, but not why you see what you see in a particular moment; the content of perception depends on current stimuli and context, not merely on the mechanism that makes vision possible.
• Conclusion: Evolutionary biology and game theory clarify the resources and constraints under which ethical reasoning occurs, but they do not provide a complete account of moral judgment or guarantee to undermine it. The talk ends by pointing to a future focus on the objective side of subjectivity in ethics.

Conceptual and Practical Takeaways

• Evolutionary theory provides mechanisms explaining cooperation and altruism (kin selection, group selection) but does not automatically justify moral norms.
• Game theory highlights how reciprocity and strategies like tit for tat can foster cooperation in repeated interactions, which resonates with intuitive ethics (reciprocity, fairness) without claiming to replace normative theory.
• The Golden Rule's convergence with tit-for-tat underlines a natural alignment between ethical ideals and strategy in social interactions.
• The potential threat hinges on the prospect that explanations (why we are ethical) could override justification (why we ought to be ethical); the speaker resists this threat, arguing that ethical choices remain under our control and are not reducible to genes or strategic payoff alone.
• The next lecture will shift emphasis to the objective dimension of ethics, complementing the subjectivist and rationalist discussions already presented.

Notable People, Works, and References Mentioned

• E. O. Wilson — sociobiology and its application to social behavior and altruism
• John von Neumann and Oskar Morgenstern — 1944, The Theory of Games and Economic Behavior
• John Nash — game theory and the popular profile in A Beautiful Mind
• Robert Axelrod — organizer of the iterated Prisoner’s Dilemma tournaments (1980, 1981)
• William Hamilton — collaborator with Axelrod on evolutionary dynamics of strategies
• Golden Rule — ancient ethical principle; origins in Egyptian and Zoroastrian literature
• Michael Roos — quoted regarding morality as an evolutionary byproduct (epiphenomenon)
• Philip Kitcher — philosopher cited on genetics, explanation, and choice
• Dawkins vs. the transcript’s misattribution: The Selfish Gene was written by Richard Dawkins; the transcript mentions Richard Daughton (likely a slip). The field’s reference remains to Dawkins’ work on evolution and altruism.

Connections to Earlier and Later Lectures

• Builds on prior discussions of cultural relevance by introducing biological and mathematical frameworks for social organization.
• Sets up themes for subsequent lectures to explore objective dimensions of subjectivity and how empirical theories interface with normative ethics.