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[일반] Word of the Day: AI code of ethics
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Daily updates on the latest technology terms | December 5, 2018
AI code of ethics

An AI code of ethics, also called an AI value platform, is a policy statement that formally defines the role of artificial intelligence as it applies to the continued development of the human race. The purpose of an AI code of ethics is to provide stakeholders with guidance when faced with an ethical decision regarding the use of artificial intelligence.

Isaac Asimov, the science fiction writer, foresaw the potential dangers of autonomous AI agents long before their development and created The Three Laws of Robotics as a means of limiting those risks. In Asimov's code of ethics, the first law forbids robots from actively harming humans or allowing harm to come to humans by refusing to act. The second law orders robots to obey humans, unless the orders are not in accordance with the first law. The third law orders robots to protect themselves, insofar as doing so is in accordance with the first two laws.

Although developers are still in the early stages of AI adoption, it's important for enterprises to take ethical and responsible approaches when creating AI systems. To that end, a non-profit institute founded by MIT cosmologist Max Tegmark, Skype co-founder Jaan Tallinn and DeepMind research scientist Viktoriya Krakovnahas -- worked with AI researchers and developers to establish a set of guiding principles which are now referred to as the Asilomar AI Principles. This AI code of ethics mandates that:

 

The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

 

Investments in AI should be accompanied by funding for research on ensuring its beneficial use.

 

If an AI system causes harm, it should be possible to ascertain why.

 

Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.

 

There should be a constructive and healthy exchange between AI researchers and policy-makers.

 

A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

 

Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

 

AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.

 

Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications.

 

Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.

 

AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.

 

People should have the right to access, manage and control the data they generate, given AI systems' power to analyze and utilize that data.

 

The application of AI to personal data must not unreasonably curtail people's real or perceived liberty.

 

AI technologies should benefit and empower as many people as possible.

 

The economic prosperity created by AI should be shared broadly, to benefit all of humanity.

 

Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.

 

The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends.

 

Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

 

An arms race in lethal autonomous weapons should be avoided.

Quote of the Day

 
"Diversity brings about different ways of thinking, different ethics and different mindsets. Together, this creates more diverse and less biased AI systems." - Kathleen Walch

Learning Center

 

Why AI for social good is a thing
The research of CMU's Fei Fang lives at the intersection of AI for social good and multi agent systems. She explains why this area of AI is important and what CIOs can glean from it in the final installment of 'Schooled in AI.'

Approaches for embedding human ethics in AI systems
Embedding ethics in AI systems is not a high priority for CIOs aiming to harness the power of machine intelligence. That's a mistake, said Darin Stewart at this week's Gartner Catalyst event. IT needs to ensure that AI systems reflect corporate and community values.

How to keep your implementation of AI free from algorithm bias
Keeping your implementation of AI free of algorithm bias can be a challenge, but data quality and model transparency are good places to start, says one Accenture consultant.

AI for finance adoption affected by legal, ethical issues
Read why using AI for finance processes could be held back by ethical and legal issues that will require people to supervise AI tools.

IBM's Rossi on AI ethics: 'Start small and widen the scope'
The rapid evolution of AI systems is prompting calls for a code of AI ethics. But how to make a moral machine is far from settled science.

Quiz Yourself

 
Before I invest time and money in a certification for mechatronics, I want to seek ______ from someone at the Robotic Industries Association (RIA).
a. counsel
b. council

Answer

Stay in Touch

 
For feedback about any of our definitions or to suggest a new definition, please contact me at: mrouse@techtarget.com

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