I have seen lots of posts talking about the “ethical” use of AI, and I have shared a few short posts on it myself, however feel it is about time for a slightly longer post having had a bit longer to think about the subject.
Ethics
Firstly lets just take a definition for ethical:
“Ethical comes from the Greek ethos “moral character” and describes a person or behavior as right in the moral sense – truthful, fair, and honest. Sometimes the word is used for people who follow the moral standards of their profession”
Vocabulary.com (as at 14/07/2023)
So for something to be ethical it needs to be truthful, fair and honest. At first glance this all seems pretty simple in who would want things to be false, unfair or dishonest? Well first thing to accept is that we will have some bad actors using AI who are not bothered in ethics, simply looking for money, to cause disruption, etc; e.g. cyber criminals using AI tools for example. But we will get to these people in a later post, just to keep things simpler for now. Lets assume for a minute that everyone is wanting to be ethical and to behave appropriately.
Ethics according to who
This is where we hit our first big problem in my eyes. Lets take truthfulness in the first instance; In some domains this might be simple to achieve, identifying what is demonstrably true (e.g. basic maths) however in our ever more complex and nuanced world it is becoming increasingly difficult to show what is true. I knew the truths that there were 9 planets in the solar system and that there was research underpinning learning styles (VAK) theory however in both cases these truths have since proven to be incorrect. The truth changed. And that’s before we get to politics, religion and football where everyone’s own truth may be slightly different, with everyone able to provide the evidence which, for them supports their own truth. So what is the truth and who will be responsible for defining it? And how will an AI scraping the internet for training data be able to tell the difference between yesterdays truth and todays new truth, my truth and your conflicting truth? Fairness and dishonesty suffer similar issues.
But this isnt new
The above isnt however limited to technology and AI, it is a societal issue. When having a discussion, when presenting or sharing ideas, purchasing and not stealing, we need to make decisions based on what is ethical, right, truthful, fair and honest, and where there might be differing views on what is right, truthful and fair. How do we deal with this in our day to day lives? Surely we must deal with it as otherwise life would grind to a hal.
The answer, in my opinion, is that we have laws that govern us plus we also have our own moral compass. We have defamation, equality and discrimination law for example. But we also have our own moral compass built from our experience and upbringing. My mother often stated to “do unto others as you expect other to do unto you” for example. For most this seems to work.
A world of AI and ethics
In a world of generative AI we still have the same laws regarding defamation, etc, so this seems to provide the same guidance in relation to ethics as provided to our wider existence in society, and we also have the same old inner compass. I, as a user of AI, should take care that content I share is truthful, fair and honest. The vendor providing the AI tool should do what they can to ensure that their tool is as truthful, fair and honest as possible, but where we need to accept this is difficult given changing truth and differing views on fairness and honesty; So in the face of these difficulties we fall back on the laws and our inner ethical compass.
I suspect the key issues here are in relation to vendors of AI solutions and how they make sure their platforms are fair, truthful and honest in the face of use across national borders with differing beliefs on fairness and with differing laws, and in the face of content being posted online where there may be accidental or purposeful malicious intent. But this challenge is no different than the very same challenge faced with social media.
The second challenge is the interface between AI and the user. If a user uses an AI solution to create an image and submits it to a competition, where the image is identified to have clear commonalities with a piece of copyrighted work, who is responsible for the copyright infringement? Is it the AI vendor for including the content in their training data or is it the user for presenting the content as original? I suspect I will post a bit further on this discussion shortly, however I previously talked briefly about it in my article in EdExec magazine here.
Conclusion
The above two issues are the main issues I see in relation to AI and ethics; Other than this I am not sure what it is we are discussing. And even here is it about ethics at all, or simply about establishing who is responsible for content coming out of generative AI solutions. How responsible are the owners of the AI solution and what responsibility does an AI user have for the content they create and use?
Ethics sounds like a good discussion point: Lets talk ethics and AI. But does it mean much? Its too broad, and much the same as the discussion of AI is a little on the broad side. If discussing ethics and AI, why not discuss technology and ethics or even just ethics itself?
I think we need to stop talking about ethics in general, in relation to AI, and get to the specifics of our concerns. Is it concerns for bias, error, mis-use, etc? And in what way is this concerning? Is it that bias in training data sets will lead to homogenised responses which therefore would be unfair and discriminatory against minority groups? And if this is the issue how is the addressed through the framework of current discrimination law and what shortfalls exist in a world of generative AI?
Lets drop the “ethics” soundbite in our discussion of AI; Of course we want use to be fair, truthful and honest, much as we want everything else in life to be fair, truthful and honest, but what specifically does this mean and how can we adjust the current frameworks in relation to fairness, truthfulness and honesty, to encompass AI.
Technology and Learning