There is no doubt that Artificial Intelligence has a number of issues that need to be addressed before its benefits can become more wide-spread. Also, if it were to become more autonomous, we would need to be able to at least anticipate its decisions and perhaps even understand how they come about. However, none of these things have proven to be happening yet. Whether that’s due to some innate infeasibility or due to some other factor is yet to be discovered.
What we have discovered though, again and again, is that most A.I. developments take the world by surprise. Even the people involved in this field, dedicated scientists and engineers who have spent countless hours working with such systems. However, our collective understanding of them still eludes us and it’s not the A.I.’s fault.
It’s easy to blame an A.I. or the people behind it for anything that goes wrong, but remember that various A.I. projects were seen to their completion because we as potential users of them wanted them out there. Whether we understood the implications of these systems or not though is questionable.
So, the biggest issue of A.I. might be how we relate to it, combined with the fact that we don’t really understand it in depth. The evangelists of the field view it as a panacea of sorts, oftentimes confusing A.I. with ML, while often considering the latter as a subfield of the former. On the other hand, the technical people involved in A.I. see it as a cool technology that can keep them relevant in the tech market. As for the consumers of A.I., they see it as a cool futuristic tech that may make life more interesting, though it may also change the dynamics of the job market in very disruptive (or even disturbing) ways. Unless, we all obtain a more clear understanding of what A.I. is, what it can and cannot do, and how it works (to the extent each person’s technical level allows), A.I. will remain an exotic technology wrapped in a mist of mystique.
That’s not an unsurmountable problem though. Nowadays, knowledge is more accessible than ever before, so if someone wants to learn about A.I. more, it’s just a matter of committing to that task and putting the hours necessary. Granted that sometimes a few books or videos would be needed too, with whatever cost this entails, still the task is a quite manageable one. Besides, one doesn’t need to be an A.I. expert in order to have sensible expectations of this tech and be able to discern the brilliance of some such systems from the BS of many of the futurists.
All in all, the more one knows about this field and the more realistic his or her expectations are, the better the chances of deriving value from A.I., without falling victim of the problems that surround it.
Zacharias Voulgaris, PhD
Passionate data scientist with a foxy flair when it comes to technology, technique, and tests.