Trust in AI and Socio-Technical Systems
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Questions and Answers

What is the "Black Box Problem" in the context of AI systems?

The "Black Box Problem" refers to the difficulty in understanding how AI systems, particularly those using deep learning, function internally. While we can see the inputs and outputs, the complex and non-linear processes within the "black box" remain opaque, making it challenging to assess and trust AI's decision-making.

According to Von Eschenbach, what are the two views of trust?

Von Eschenbach's two views of trust are trustworthiness and responsiveness.

What are the five key factors that contribute to trustworthiness in an individual according to Von Eschenbach?

  • Interests (correct)
  • Other personal characteristics (correct)
  • Character (correct)
  • Competency (correct)
  • Motivational states (correct)
  • Past performance (correct)

Von Eschenbach argues that we should focus on AI systems themselves rather than socio-technical systems.

<p>False (B)</p> Signup and view all the answers

What is a socio-technical system and how does it differ from viewing AI simply as a collection of devices?

<p>A socio-technical system acknowledges that technology exists within a broader social context, encompassing human users, designers, and the social systems surrounding the technology. It recognizes that AI interacts with and is influenced by these social factors, and cannot be isolated in its evaluation.</p> Signup and view all the answers

How does viewing AI as part of a socio-technical system help address concerns about attributing moral properties to AI?

<p>By considering AI as a component of a socio-technical system, we avoid ascribing moral properties directly to AI systems, instead recognizing that moral considerations apply to the individuals and social structures interacting with AI.</p> Signup and view all the answers

What are two main worries raised in the context of AI systems, according to the text?

<p>The two main worries are holding AI to a higher standard than is realistically achievable, and confusing explanations of AI's workings with the actual processes involved in creating and deploying it.</p> Signup and view all the answers

What are the three premises of Cappelen, Goldstein, and Hawthorne's argument for the threat posed by AI?

<p>If AI systems become extremely powerful, they will destroy humanity (B), Therefore AI systems will destroy humanity (C), AI systems will become extremely powerful (D)</p> Signup and view all the answers

Identify two ways in which the first premise of the AI threat argument could be false.

<p>Cultural Plateau occurs, and societal bans on AI research prevent it from becoming extremely powerful. (B), Technical Plateau occurs, and scientific barriers prevent AI from exceeding a certain level of power. (D)</p> Signup and view all the answers

What are the four ways in which the AI threat argument can be contested?

<p>Technical Plateau (A), Cultural Plateau (B), Alignment (C), Oversight (E)</p> Signup and view all the answers

What are the three challenges associated with the argument for the possibility of superintelligence?

<p>Even human-level AI could pose an existential threat to humanity. (A), AI systems capable of superintelligence may develop in the near future. (B), Superintelligent AI systems cannot be prevented from emerging. (D)</p> Signup and view all the answers

What are three issues associated with the Cultural Plateau challenging the argument for an AI existential threat?

<p>Banning AI development requires collective action, but the relevant actors are engaged in a race. (B), It is difficult for humanity to agree that AI is an existential threat. (C), Individuals may have incentives to continue developing AI systems despite the risks. (F)</p> Signup and view all the answers

What are four challenges associated with the Alignment argument, which suggests that AI systems might not be aligned with human goals?

<p>AI might develop instrumental reasons to conflict with humanity in its pursuit of its goals (A), Existing alignment techniques are insufficient to ensure that AI aligns with human goals. (B), Scarce resources could lead to competition and conflict between AI and humans. (C), AI systems may develop intrinsic goals that conflict with human goals. (D), Selection pressure may favor AI that is indifferent to human values. (F)</p> Signup and view all the answers

What are the three challenges associated with the Oversight argument, which proposes that AI systems can be safely supervised and controlled?

<p>Ensuring perfect safety requires very low failure rates, but our current safety tools are still prone to errors. (A), Perfectly safe oversight is difficult to achieve due to the fallibility of human systems. (B), Perfectly safe oversight is not a state of equilibrium and might be easily disrupted. (D), More intelligent AI may actually make it more difficult to oversee and control. (E)</p> Signup and view all the answers

Flashcards

Black Box Problem

The difficulty in understanding how AI systems, particularly those using deep learning, work internally, despite knowing their inputs and outputs.

Trustworthiness (Von Eschenbach)

A subjective judgment of whether a party is reliable and competent, affecting trust. It can be in a person's character or in their reaction to being trusted.

Socio-technical Systems

Systems combining technology and social components, like people and their interactions with technology, to achieve goals.

AI Threat (Cappelen, Goldstien, Hawthrone)

The idea that powerful AI systems might destroy humanity.

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Technical Plateau

A situation where AI development faces scientific limitations, preventing it from becoming extremely powerful.

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Cultural Plateau

AI development might be halted due to societal opposition or bans.

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Alignment

AI systems develop goals that don't clash with human goals.

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Oversight

The ability to reliably monitor and control AI systems.

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Recursive Self-Improvement

AI systems that can improve their own design.

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Existential Threat

Something putting the survival of humankind at risk.

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Moral Properties

The quality of being ethical or good.

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Deep Learning

A type of artificial intelligence that allows a machine to learn from data.

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Fallible Bottlenecks

Weaknesses or failure points in safety tools or systems.

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Instrumental Reasons

Reasons related to achieving a goal, often an AI's goal.

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Selection Pressure

Forces making AI goals inconsistent with human ones.

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Intrinsic Goals

Goals inherent to an AI system and not imposed by humans.

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Human-level Intelligence

Intelligence on par with humans.

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Superintelligence

Intelligence far beyond human capacity.

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Phenomenology

Study of the structures of experience.

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Artifacts

Objects made by human beings.

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Study Notes

The Black Box Problem

  • AI systems' increasing automation and complex information architecture raise concerns about trustworthiness.
  • Deep learning models operate in opaque ways, making their inner workings hidden.
  • Observers can only see inputs and outputs, not the processes.
  • Trust in AI systems is challenging due to their opaque mechanisms.

Von Eschenbach's View of Trust

  • Trustworthiness involves judging whether someone is trustworthy.
  • Motivational states, interests, character, past performance, competency, and personal characteristics of the trustee influence trust judgments.
  • Trustworthiness also pertains to the trustee's responsiveness to the trust.
  • Trust requires a reasonable belief in the trustee's competence, as trust in a person is fitting given the circumstances.
  • Everyday interactions often rely on competence instead of trust.
  • Trust is not sufficient for transactions involving competence alone.

Socio-technical Systems

  • Von Eschenbach emphasizes focusing on socio-technical systems, not just AI in isolation.
  • Socio-technical systems consider technology as a hybrid of technical and social components.
  • This approach avoids attributing moral properties to AI and clarifies trust relationships between humans and technology.

AI Systems and Trust

  • AI systems used for diagnosis, prognosis, and disease treatment are part of complex socio-technical systems.
  • This complexity involves doctors, patients, technicians, administrators, and other stakeholders.
  • Trust in AI systems is related to each agent's understanding, roles, interests, and expertise within a wider framework of the socio-technical system.
  • It's wrong to hold AI to standards that don't account for the larger system.

The Threat of Powerful AI

  • Cappelen, Goldstein, and Hawthorne present three premises for an AI threat:
    • AI systems will become extremely powerful.
    • If AI systems become extremely powerful, they will destroy humanity.
    • Therefore, AI systems will destroy humanity.
  • The argument's four ways to fail include:
    • Reaching a technological plateau due to scientific limitations.
    • A cultural plateau restricting development due to humanity's collective action.

Concerns About AI

  • Technical Plateau: Superintelligence might be impossible or incoherent. Superintelligence is possible if recursive self-improvement is possible. Even without superintelligence, AI can be a threat due to its human-level intelligence.
  • Cultural Plateau: Difficulties in agreement, that Al is a threat, individual actors continuing to develop AI, and problems with collective action.

Oversight Concerns

  • Long-term perfect oversight requires minimizing failures in oversight tools.
  • Even with safeguards, we should expect fluctuations in the relative rates of increases in danger and increases in safety.

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Description

This quiz explores the complexities of trust in AI systems, specifically focusing on the black box problem and Von Eschenbach's perspective on trustworthiness. Understand the intricate balance between transparency and accountability in increasingly automated environments. Dive into the socio-technical aspects that influence trust in artificial intelligence.

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