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Building an ethical policy for AI

Jonathan Ebsworth
|Jul 6|magazine16 min read

It’s easy to be ethical. We are all faced with obvious choices between right and wrong, and most of us try to choose the right path – don’t steal, don’t lie, don’t do harm. It’s only rarely that a person or organization decides to do something that’s patently wrong.

Sometimes, however, doing the right thing is difficult; not least when it concerns a new technology where we’re unsure of the impact that it will have on our lives. Artificial intelligence (AI) is one such technology. Because it’s still very much in its infancy, full of potential but with its ethical implications largely unmapped, our enthusiasm for its potential can blind us to its potentially harmful side-effects.

Take Google’s recent demonstration of its Duplex technology. Let’s be clear: passing the Turing Test is a momentous milestone in the history of AI, and Google’s engineers should be proud of their achievement – but it’s a problematic one. What’s worrying is that Duplex, proof-of-concept though it is, is engineered with deception at its heart.

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At no point in the demonstration does the AI inform its human interlocutor that it’s a bot, and this runs directly contrary to the House of Lords’ recently-published AI Code, the fifth tenet of which states that “the autonomous power to hurt, destroy or deceive human beings should never be vested in artificial intelligence.”

Duplex’s duplicity is only one example of the ethical minefield into which we are blindly stumbling. Every business is rushing to develop new AI-powered applications which will undoubtedly change our lives. Whether they are for the better or for the worse will depend on whether businesses tackle the tricky ethical questions inherent in such a transformative technology.

Businesses may think that such concerns are a matter for regulators and legislators, but this would be an historic mistake. Consumers don’t mind too much about intentions or whether a company has acted legally. They care about outcomes; if an unethical AI application causes them harm, then it will damage its creator just as much as if they really had had evil aims.

Ethics clearly makes good business sense, but committing to an ethical AI policy is the easy bit. Much harder at this nascent stage is actually to create a meaningful ethical policy that protects users without hindering innovation. How, then, can we cut the Gordian Knot of ethical AI?

The House of Lords’ AI Select Committee’s report, mentioned above, is as good a place as any to start, with its commitment to AI that is developed for the common good of everyone, operates on the principles of intelligibility and fairness, protects privacy, and does not harm humanity.

There are other organizations working on this topic. Perhaps the most advanced is the work done by the Institute of Electrical and Electronics Engineers (IEEE) with its Ethically Aligned Design framework, which aims to define values and ethical principles for intelligent and autonomous systems. The IEEE is sponsoring the creation of standards (such as IEEE P7000™ series) and future certification programmes. Other ideas and frameworks include the Department for Digital, Culture, Media and Sport’s (DCMS) Centre for Data Ethics and Innovation, and the Ada Lovelace Institute which is examining the ethical and social issues arising from new technologies such as AI.

Clearly there is no shortage of activity, but these initiatives are still inchoate; businesses developing AI today cannot afford to wait for a consensus to form around ethics. They need to take action to create a policy that prevents them from creating applications that are open to abuse or which, unwittingly, could cause us harm. So, what should we consider when creating an ethical policy for AI?

1) Goals

The intentions of such a policy should be to consider holistically the impact of the solutions we create and confirm that they are consistent with the values of our business. Above all, we should be concerns with creating lasting value both for our shareholders and for society – not some ephemeral, selfish aim – like Enron’s efforts to boost its share price at all costs.

2) Approach

To ensure we succeed, we need teams to be fully aware of, and sharing, our business values; that are focused on lasting value rather than ‘big ideas’; and are supported and rewarded through our policies and processes. Above all, they must appreciate the significance and positive value of sound business ethics so that they can ensure the lasting value of the applications they create.

This requires strong leadership with the ability to manage ethical risk at three levels of the development process. At the individual or creative group level, we need people to consider the ethical implications of their ideas; at the business function level, we should formalise this assessment with appropriate actions associated with the identified level of risk; finally, operational management should be highly engaged throughout the process to map and monitor these risks against business goals. Management’s attitude towards these issues will go a long way towards setting the tone towards ethics in our business.

3) Commitment

There will be winners and losers in the race to AI, but those who succeed will be those that develop applications that are deemed ethically acceptable or, better, beneficial to society. We can choose to rely on luck – or we can commit wholeheartedly to pursuing an ethical path.

4) Outcome

Done right, ethics can strengthen our brand, reinforce our values, provide competitive advantage and create enhanced value. Done carelessly, we are putting our hard-won reputation on the line – along with the safety and security of every stakeholder. That alone should make us think very carefully about our approach to AI initiatives.

Artificial intelligence itself is amoral; it is how we use our creation that will determine its effects on humanity. Let us approach the AI-powered future in a spirit of hope tempered with caution.  If we are open about our commitment to ethics, then we can realize our greatest hopes for AI – and reap the benefits of being seen to do the right thing.

Jonathan Ebsworth, Partner, Infosys Consulting