(15) Bias on Machine

Without clear technical judgement, human cannot have bias on AI when human and AI shows similar risks.
Principle: Harmonious Artificial Intelligence Principles (HAIP), Sep 16, 2018

Published by HAIP Initiative

Related Principles

Fairness and inclusion

AI systems should make the same recommendations for everyone with similar characteristics or qualifications. Employers should be required to test AI in the workplace on a regular basis to ensure that the system is built for purpose and is not harmfully influenced by bias of any kind — gender, race, sexual orientation, age, religion, income, family status and so on. AI should adopt inclusive design efforts to anticipate any potential deployment issues that could unintentionally exclude people. Workplace AI should be tested to ensure that it does not discriminate against vulnerable individuals or communities. Governments should review the impact of workplace, governmental and social AI on the opportunities and rights of poor people, Indigenous peoples and vulnerable members of society. In particular, the impact of overlapping AI systems toward profiling and marginalization should be identified and countered.

Published by Centre for International Governance Innovation (CIGI), Canada in Toward a G20 Framework for Artificial Intelligence in the Workplace, Jul 19, 2018

5. Non Discrimination

Discrimination concerns the variability of AI results between individuals or groups of people based on the exploitation of differences in their characteristics that can be considered either intentionally or unintentionally (such as ethnicity, gender, sexual orientation or age), which may negatively impact such individuals or groups. Direct or indirect discrimination through the use of AI can serve to exploit prejudice and marginalise certain groups. Those in control of algorithms may intentionally try to achieve unfair, discriminatory, or biased outcomes in order to exclude certain groups of persons. Intentional harm can, for instance, be achieved by explicit manipulation of the data to exclude certain groups. Harm may also result from exploitation of consumer biases or unfair competition, such as homogenisation of prices by means of collusion or non transparent market. Discrimination in an AI context can occur unintentionally due to, for example, problems with data such as bias, incompleteness and bad governance models. Machine learning algorithms identify patterns or regularities in data, and will therefore also follow the patterns resulting from biased and or incomplete data sets. An incomplete data set may not reflect the target group it is intended to represent. While it might be possible to remove clearly identifiable and unwanted bias when collecting data, data always carries some kind of bias. Therefore, the upstream identification of possible bias, which later can be rectified, is important to build in to the development of AI. Moreover, it is important to acknowledge that AI technology can be employed to identify this inherent bias, and hence to support awareness training on our own inherent bias. Accordingly, it can also assist us in making less biased decisions.

Published by The European Commission’s High-Level Expert Group on Artificial Intelligence in Draft Ethics Guidelines for Trustworthy AI, Dec 18, 2018

5. The autonomous power to hurt, destroy or deceive human beings should never be vested in artificial intelligence.

There is a significant risk that well intended AI research will be misused in ways which harm people. AI researchers and developers must consider the ethical implications of their work. The Cabinet Office's final Cyber Security & Technology Strategy must explicitly consider the risks of AI with respect to cyber security, and the Government should conduct further research as how to protect data sets from any attempts at data sabotage. The Government and Ofcom must commission research into the possible impact of AI on conventional and social media outlets, and investigate measures which might counteract the use of AI to mislead or distort public opinion as a matter of urgency.

Published by House of Lords, Select Committee on Artificial Intelligence in AI Code, Apr 16, 2018

7. Principles of human dignity and individual autonomy

Users should respect human dignity and individual autonomy in the utilization of AI systems or AI services. [Main points to discuss] A) Respect for human dignity and individual autonomy With consideration of social contexts in the utilization of AI, users may be expected to respect human dignity and individual autonomy. B) Attention to the manipulation of human decision making, emotions, etc. by AI Users may be expected to pay attention to the risks of the manipulation of human decision making and emotions by AI and risks of excessive dependence on AI. It is crucial to consider who takes what measures against such risks. C) Reference to the discussion of bioethics, etc. in the case of linking AI systems with the human brain and body When linking AI with the human brain and body, users may be required to particularly take into consideration that human dignity and individual autonomy will not be violated, in light of discussions on bioethics, etc.

Published by Ministry of Internal Affairs and Communications (MIC), the Government of Japan in Draft AI Utilization Principles, Jul 17, 2018

Human computer symbiosis

Relation between AI and human is not an either or relationship, on the contrary, AI can and should enhance human wisdom and creativity

Published by Pony Ma, founder, chairman and CEO of Tencent in The ARCC (Available, Reliable, Comprehensible, and Controllable) for AI, Sep 18, 2018