Towards Ethical AI: A Guide for Businesses
The rise of Artificial Intelligence (AI) technologies has significantly impacted various sectors, revolutionizing the way businesses operate.
Most companies that claim to care about AI ethics are lying. Not maliciously, but in the way organizations always lie when they publish principles they have no real mechanism to enforce. "We value fairness and transparency" sounds great until someone has to choose between shipping a product on time and auditing its bias.
A study from 2017-2019 interviewed 23 AI ethics managers at major tech companies. What they found was telling: principles alone don't work. You can write "respect human dignity" on a poster, but that doesn't help a developer decide whether to include certain data in a training set.
What actually matters
The companies that took ethics seriously built actual structures: ethics officers with real authority, review committees that could block products, checklists that engineers had to complete before launch. The ones that just published principles and moved on accomplished nothing.
The study identified the obvious risks: privacy violations, algorithmic bias, job displacement, misinformation. Nothing surprising there. What was more interesting was why companies bothered at all. It wasn't altruism. They were protecting themselves against regulation, maintaining customer trust, and trying not to become the next Cambridge Analytica.
Self-interest dressed up as ethics can still produce good outcomes. I'm not sure I care about the motivation if the result is fewer discriminatory algorithms.
The honest answer
Nobody has this figured out. The law is years behind the technology. The ethics frameworks are too abstract to apply. The academics writing papers don't have to ship products. The companies shipping products don't have time to read academic papers.
What works, at least somewhat: making someone's job depend on catching problems before they happen. Creating friction in the development process that forces people to think. Getting input from people who will actually be affected by the system. None of this is glamorous. It's just organizational hygiene.
If your company has AI ethics principles but no ethics officer who can kill a project, the principles are marketing.
Based on "What is ethical AI?" from The Conversation.
