Just Asking

Today I started to ask questions within me. I have been an outspoken critic on the fact of AI and knowing it doesn’t exist questions came to mind. Question that, as I see it the BBC isn’t asking either. So lets get to this game and let you work out what is real.

Phase One
In phase one we look at AI and the data, you see any deeper machine learning solution (whether you call it AI or not) will depend on data. Now we get that no matter what you call this solution it will require data. Now that Deeper Machine Learning and LLM solutions require data (as well as the fact that the BBC is throwing article after article at us) who verifies the data?

Consider that these solutions have access to all that data, how can any solution (AI or not) distinguish the relevant data? We get the BBC in January give us this quote “That includes both smaller, specialist AI-driven biotech companies, which have sprung up over the past decade, and larger pharmaceutical firms who are either doing the research themselves, or in partnership with smaller firms.” My personal issue is that they all want to taste from the AI pie and there are many big and small companies vying for the same slice. So who verifies the data collected? If any entry in that data sphere requires verification, what stops errors from seeping through? This could be completely unintentional, but it will happen. And any Deeper Machine Learning system cannot inspect itself. It remains a human process. We will be given a whole range of euphemistic settings to dance around that subject, but in short. When that question is asked, the medical presenter is unlikely to have the answer and the IT person might dance around the subject. Only once did I get a clear answer from a Chinese data expert “We made an assumption on the premise of the base line according to the numbers we have had in the past”, which was a decent answer and I didn’t expect that answer making it twice as valuable. There is the trend that people will not know the setting and in the now there is as I see it, a lack of verification. 

Phase Two
Data Entry is a second setting. As the first is the verification of data that is handled, the second question is how was this data entered? It is that setting and not the other way round. You must have verifiable data to get to the data entry part. If you select a million parameters, how can you tell if a parameter is where it needs to be? And then there is a difference between intrinsic and extrinsic data. What is observed and what is measured. Then we get to the stage that (as the most simple setting) that are the Celsius and Fahrenheit numbers correct (is there a C when if should be an F) you might think that it is obvious, but there are settings when that is a definite question mark. Again, nothing intentional, but the question remains. So when we consider that and Deeper Machine Learning comes with a guidance and all this comes from human interactions. There will be questions and weirdly enough I have never seen them or seen anyone ask this (looking way beyond the BBC scope).

Phase Three
This is a highly speculative part. You see environment comes into play here and you might have seen it on a vacation. Whilst the locals enjoy market food, you get a case of the runs. This is due to all kinds of reasons. Some are about water and some about spices. As such the locals are used to the water and spices but you cannot handle either. This is an environmental setting. As such the data needs to be seen with personal medical records and that is a part we often do not see (which makes sense), but in that setting how can any solution make a ‘predicted’ setting when part of that data is missing?

So, merely looking at these three settings. I have questions and before you think I am anti-AI. I am not, it merely doesn’t exist yet and whilst the new Bazooka Joe’s are hiding behind the cloak of AI, consider that all this require human intervention. From Data Entry, to verification and the stage of environmental factors. So do you really think that an Indian system will have the same data triggers as a Swedish one? And consider that I am merely asking questions, questions the BBC and many others aren’t seemingly asking.

So take a moment to let that shift in and consider how many years we are away from verified data and now consider all the claims you see in the news. And this is only the medical field. What other fields have optionally debatable data issues?

Have a great day and when Mr. Robot say all is well, make sure you get a second opinion from a living GP.