Artificial Intelligence, Values and Alignment

@article{Gabriel2020ArtificialIV,
  title={Artificial Intelligence, Values and Alignment},
  author={Iason Gabriel},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.09768}
}
This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values… 

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References

SHOWING 1-10 OF 109 REFERENCES

Expected Utilitarianism

TLDR
It is shown that if one believes that a beneficial AI is an ethical AI, then one is committed to a framework that posits 'benefit' is tantamount to the greatest good for the greatest number, and if the AI relies on RL, then the way it reasons about itself, the environment, and other agents, will be through an act utilitarian morality.

Social choice ethics in artificial intelligence

TLDR
The normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society, and the design of social choice AI faces three sets of decisions.

The global landscape of AI ethics guidelines

TLDR
A detailed analysis of 84 AI ethics reports around the world finds a convergence around core principles but substantial divergence on practical implementation, highlighting the importance of integrating guideline-development efforts with substantive ethical analysis and adequate implementation strategies.

Artificial Intelligence: the global landscape of ethics guidelines

TLDR
A global convergence emerging around five ethical principles (transparency, justice and fairness, non-maleficence, responsibility and privacy), with substantive divergence in relation to how these principles are interpreted; why they are deemed important; what issue, domain or actors they pertain to; and how they should be implemented.

The Arc of the Moral Universe and Other Essays

In this collection of essays, Joshua Cohen locates ideas about democracy in three far-ranging contexts. First, he explores the relationship between democratic values and history. He then discusses

Justification and Legitimacy*

In this essay I will discuss the relationship between two of the most basic ideas in political and legal philosophy: the justification of the state and state legitimacy. I plainly cannot aspire here

Normative Uncertainty as a Voting Problem

Some philosophers have recently argued that decision-makers ought to take normative uncertainty into account in their decisionmaking. These philosophers argue that, just as it is plausible that we

Value Alignment or Misalignment - What Will Keep Systems Accountable?

TLDR
It is proposed that a hybrid approach for computational architectures still offers the most promising avenue for machines acting in ethics and critically considers how such an approach can engage the social, norm-infused nature of ethical action.

Social Choice and the Value Alignment Problem *

Principles alone cannot guarantee ethical AI

TLDR
Significant differences exist between medical practice and AI development that suggest a principled approach may not work in the case of AI, and Brent Mittelstadt highlights these differences.
...