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AI ethics: Why it’s gone from emergent to urgent

Our society runs on automated algorithms. From the energy grids that power our homes to the healthcare systems that keep us well and even the food in our grocery stores, so much relies on a delicate balance of machine learned automation.

But these data driven systems must be principled if they are to represent and respect our collective agency and individual diversity.

As researcher and anthropologist S. A. Applin, PhD, recently told FastCompany, “The ‘ethics’ that are informing digital technology are essentially biased, and many of the proposals for ethics in AI – developed as they are by existing computer scientists, engineers, politicians and other powerful entities – are flawed, and neglect much of the world’s many cultures and ways of being.”

Many of the proposals for ethics in AI are flawed, and neglect much of the world’s many cultures and ways of being.

So what does all this mean for your business and how can committing to ethical AI help your work, and the systems you use to do it, thrive? Let’s start with the basics.

What does “ethical AI” even mean?

Coined in the 1950s, AI isn’t “new.” However, it still borders on emergent – and so does a clear definition of its ethics.

The closest thing to a consensus on ethical AI is a set of standards from the European Commission, titled “Ethics Guidelines for Trustworthy AI.

Per the guide, for AI to be considered “trustworthy” it should be:

1. Lawful: Respecting all applicable laws and regulations…

2. Ethical: Respecting ethical principles and values…

3. Robust: Both from a technical perspective, while taking into account its social environment

The Guidelines also recommend seven individual requirements that are key for ethical AI systems, including:

  • Human agency and oversight
  • Technical robustness and safety
  • Privacy and data governance
  • Transparency
  • Diversity, non-discrimination and fairness
  • Societal and environmental well-being
  • Accountability

Why your business needs an AI plan – even if you aren’t using AI yet

Regardless of your industry, or even individual department, AI is inescapable. Even if you aren’t using AI yet, at some point you probably will be. And it might come sooner than you think.

According to Gartner, 80% of emerging technologies will have AI foundations by 2021.

80% of emerging technologies will have AI foundations by 2021.

AI has already become the new gold standard for processes like automating customer support, optimizing sales and marketing initiatives and using machine learning to assist IT teams with threat prevention.

Any potentially disruptive change to your business requires a plan. AI is no different. Implementing an AI plan will help ensure you help lead your company into the future instead of being dragged there.

Why should you incorporate ethics into this plan?

Ethics must be at the helm of your AI plan. Since machine learning is designed to better itself based on automated computation of deep datasets, building some human oversight into your plan can help it from going in an unintentionally unbiased direction.

One recent example of unchecked AI? Amazon’s discontinuation of an AI-run recruiting tool, which made news for being biased against female applicants.

However, the UNI Global Union’s Top Ten Principles for Ethical AI sums it up best:

“Artificial intelligence must put people and planet first. This is why ethical AI discussions on a global scale are essential. A global convention on ethical AI that encompasses all is the most viable guarantee for human survival. “

What does ethical AI look like?

Ethical AI is deeply rooted in essentials like context, cultural awareness, diversity and sociability. It’s updated with the times and culturally sensitive. For AI to be ethical, it must be inclusive so as not to reflect the gender, socioeconomic status or beliefs of the engineer or programmer in charge. It must also work for the equity of all instead of the benefit of a few.

What must ethical Al encompass? We’ll leave you with this quote from S. A. Applin:

“Artificial intelligence must be developed with an understanding of who humans are collectively and in groups (anthropology and sociology), as well as who we are individually (psychology) and how our individual brains work (cognitive science), in tandem with current thinking on global cultural ethics and corresponding philosophies and laws.”