I work at a financial institution in the United States and have been researching the regulatory impacts of Artificial Intelligence recently - specifically the simple purpose-specific systems we have today like Alexa, Siri, or the AI that navigates your Tesla when you switch on autopilot. Based on some googling  , the current standards seem to be that there aren't a lot of specific regulations that apply to the AI agent (with the exception of self-driving cars), but the normal regulations that apply when using a human agent would apply if you substitute an AI-based decision process. The top answer on a related topic here on StackExchange seems to support the idea that the regulations applied to the human apply to the AI agent as well (at least in Hong Kong).
We're currently shying away to research into the legal implications of AIs that can learn any task, much like a human. These are sometimes referred to as Artificial General Intelligence (AGIs) and the most aggressive estimate I've seen in my research places them emerging sometime in the next 100 - 200 years. A problem for future generations!
This raises a couple of questions in my mind about a couple of legal concepts that have clear definitions when applied to a human or certain kinds of AI, but get fuzzy with other ones. Specifically:
- How do you determine an AI agent's intent?
- How can you tell if an AI agent is biased in its decisions?
- How would the concept of discrimination apply to an AI agent? How would you prosecute it?
A Specific Example:
For instance, take the anti-discrimination provisions of the Equal Credit Opportunity Act (ECOA). In the case of a decision-tree based AI agent discrimination is obvious - if you add in a rule that makes different decisions based on race, gender, age, or other protected factors you have a discriminatory model.
In the case of a statistically driven Machine Learning model, this is less obvious. For instance, a neural network based model could accept address data as part of its decision. After examining hundreds of thousands of credit applications, the machine learning model could potentially derive information about income distribution from address or similar fields and end up discriminating against applicants that match certain traits. In this case you accept no information on age, sex, or ethnicity but still discriminate based on these factors since the model found some problematic trends in the data that it was trained on.
With this in mind, my questions are:
- What are your thoughts on regulations that refer to intent or bias as they relate to AI agents - particularly ones that don't operate on explicitly defined rules?
- Is there any precedent in this space that we could look to to guide decisions on AI risk?
- Does anyone have thoughts on where regulation in this space might head?
I've removed the portions of this question with a technical lean and posted a question about the technical aspects of detecting and fixing a discriminatory model to ai.stackexchange.