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AI Ethics

The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration

Wirtz, Weyerer & Sturm (2020)

Category

Risk Domain

7AI System Safety, Failures & Limitations

AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.

"Ethical challenges are widely discussed in the literature and are at the heart of the debate on how to govern and regulate AI technology in the future (Bostrom & Yudkowsky, 2014; IEEE, 2017; Wirtz et al., 2019). Lin et al. (2008, p. 25) formulate the problem as follows: “there is no clear task specification for general moral behavior, nor is there a single answer to the question of whose morality or what morality should be implemented in AI”. Ethical behavior mostly depends on an underlying value system. When AI systems interact in a public environment and influence citizens, they are expected to respect ethical and social norms and to take responsibility of their actions (IEEE, 2017; Lin et al., 2008)."(p. 821)

Entity— Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent— Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal

Other

Without clearly specifying the intentionality

Timing— Whether the risk is pre- or post-deployment

Pre-deployment

Occurring before the AI is deployed

Post-deployment

Occurring after the AI model has been trained and deployed

Other

Without a clearly specified time of occurrence

Sub-categories (4)

AI-rulemaking for human behaviour

"AI rulemaking for humans can be the result of the decision process of an AI system when the information computed is used to restrict or direct human behavior. The decision process of AI is rational and depends on the baseline programming. Without the access to emotions or a consciousness, decisions of an AI algorithm might be good to reach a certain specified goal, but might have unintended consequences for the humans involved (Banerjee et al., 2017)."

7.3 Lack of capability or robustness

AI systemOtherPost-deployment

Compatibility of AI vs. human value judgement

"Compatibility of machine and human value judgment refers to the challenge whether human values can be globally implemented into learning AI systems without the risk of developing an own or even divergent value system to govern their behavior and possibly become harmful to humans."

7.3 Lack of capability or robustness

OtherIntentionalOther

Moral dilemmas

"Moral dilemmas can occur in situations where an AI system has to choose between two possible actions that are both conflicting with moral or ethical values. Rule systems can be implemented into the AI program, but it cannot be ensured that these rules are not altered by the learning processes, unless AI systems are programed with a “slave morality” (Lin et al., 2008, p. 32), obeying rules at all cost, which in turn may also have negative effects and hinder the autonomy of the AI system."

7.3 Lack of capability or robustness

AI systemUnintentionalPost-deployment

AI discrimination

"AI discrimination is a challenge raised by many researchers and governments and refers to the prevention of bias and injustice caused by the actions of AI systems (Bostrom & Yudkowsky, 2014; Weyerer & Langer, 2019). If the dataset used to train an algorithm does not reflect the real world accurately, the AI could learn false associations or prejudices and will carry those into its future data processing. If an AI algorithm is used to compute information relevant to human decisions, such as hiring or applying for a loan or mortgage, biased data can lead to discrimination against parts of the society (Weyerer & Langer, 2019)."

1.1 Unfair discrimination and misrepresentation

AI systemUnintentionalOther