Chatbots are not capable of understanding, or analysis, or even differentiating between truth and fiction. All they can do is fit together something that looks like language. Which makes it desperately worrying when teachers use them for marking, lawyers use them for coming up with arguments to use in court, or they get used for anything requiring analysis or accuracy.
Tag: Artificial Intelligence
Teacher Guide to AI – please help!
We must educate ourselves, and our children, to be in a position to be rationally sceptical of technological hype. As a society, we need some inoculation against magical technological thinking. But where do teachers and schools start? Without a background in Artificial Intelligence, how can we expect teachers to inoculate our kids against the hype? How do we teach them to be more savvy and compassionate consumers and makers of technology? That’s where we come in. Laura Summers from Debias AI and Dr Linda McIver from the Australian Data Science Education Institute are putting together a teacher’s guide to AI, but we need your help to make sure the guide is exactly what you need. To that end we’ve put together a survey. We would love it if you could fill it out and share it with all of your teacher friends.
Lies, Damned Lies, and AI
In which I rant about tech companies marketing chatbots that are not fit for purpose. People keep telling me this tech can only improve, so I gave it the benefit of the doubt, and threw it one of the tests that often causes me grief in my attempts to dine out or at people's houses. Is this product gluten free?
There is no existential threat, ChatGPT is an evolutionary dead end
I think this is the real danger of AI - that we want to believe. Chatbots are so plausible they draw us in, even when we should know better. They give confident, and completely wrong answers, in a way that we are all too happy to accept. They seem to have generated a veneer of respectability and credibility which is wholly unearned.
Machines are unbiased, and other bedtime stories
When we use machine learning for really important things like recruitment and health, we need to be immensely cautious and rationally sceptical of the results that we get.