Google, Facebook and Microsoft are working on the ethics of artificial intelligence. Here’s what your business should do

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The ethics of AI

Kuppering Cole

As AI is making its way into more companies, the board of directors and senior executives need to mitigate the risk of their AI-based systems. One area of ​​risk includes the reputational, regulatory, and legal risks of AI-driven ethical decisions.

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AI-based systems often find themselves having to make decisions that have not been incorporated into their models decisions that represent ethical dilemmas.

For example, suppose a company creates an AI-based system to optimize the number of advertisements we see. If so, AI can encourage incendiary content that causes users to get angry, comment, and post their opinions. If it works, users spend more time on the site and see more ads. The AI ​​did its job without ethical oversight. The unintended consequence is the polarization of users.

Examples

What if your company builds a system that automates work so that it no longer needs that employee? What is the ethical responsibility of the company towards that employee, towards the company? Who is determining the ethics of the employment impact?

What if the AI ​​tells a loan officer to advise against providing a loan to a person? If the human being doesn’t understand how AI came to that conclusion, how can he know if the decision was ethical or not? (see How AI Can Go Terribly Wrong: 5 Prejudices That Create Failure)

Let’s assume the data used to train your AI system doesn’t have enough data on specific classes of individuals. If so, he may not learn what to do when he meets those individuals. Would a facial recognition system used for check-in at a hotel recognize a person with freckles? If the system stops working and makes it more difficult for a person with freckles to check in, what should the company do? How does the company address this ethical dilemma? (see Why are tech companies abandoning facial recognition?)

If developers who identify the data to be used to train an AI system are not looking for bias, how can they prevent an ethical dilemma? For example, suppose a company has historically hired more men than women. If so, there is likely to be a bias in the resume data. Men tend to use different words than women on their resumes. If the data comes from men’s resumes, women’s resumes might be viewed less favorably, based on the choice of words alone.

Ethical principles for companies

Google, Facebook and Microsoft are addressing these ethical issues. Many have pointed to the missteps Google and Facebook have taken in trying to address the ethical issues of AI. Let’s take a look at some of the positive elements of what they and Microsoft are doing to address the ethics of AI.

While every company approaches these principles differently, we can learn a lot by examining their commonalities. Here are some basic principles they address.

Fairness: AI systems should treat all people fairly and avoid creating or reinforcing unfair biases Inclusiveness: AI systems should empower everyone and engage people and include cultural diversity Reliability and safety: intelligence systems artificial intelligence systems should work reliably and securely to avoid unwanted results Transparency: artificial intelligence systems should be understandable and explainable Privacy and security: artificial intelligence systems should be safe and respect privacy and provide guarantees for privacy Accountability: systems of artificial intelligence should have algorithmic responsibility to enable proper human direction and control

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While these tech giants are flawed, they are leading the way in addressing the ethical challenges of AI. What are the board of directors and senior management team doing to address these issues?

Tips

Below are some tips you can implement now.

Transform AI ethics into board-level discussion Examine the different risks associated with AI ethics Make sure senior executives understand how and where AI-based systems are considered and implemented Develop an approach to building systems that consider ethical dilemmas before the system is built

By addressing these issues now, your business will reduce the risks that AI can make or recommend decisions that endanger the business. (see Artificial Intelligence Can Be Dangerous – How to Reduce Risk When Using AI) Are you aware of the reputational, regulatory, and legal risks associated with your AI ethics?

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