IEEE Future Directions
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I am involved, as I pointed out in a previous post, in an IEEE group trying to look at the crystal ball to imagine what the world will be like, for what concerns the IEEE landscape and business opportunities, in 2050. The core biz of IEEE today, and it has been so for the last 60 years. is the sharing of peer reviewed information, in form of articles, conferences and education courses (there is more but that is the real core).
- Too much information
The problem. already visible today, is that there is TOO MUCH information, to the point that digesting it is impossible on a human scale. Yes. in these last decades IEEE has endeavour to make information more easily accessible but that does not solve the problem of the overload of information (in a way it makes it worse). Notice, also, that the flooding of articles and the likes is a consequence of the Goodhart’s law:
“When a measure becomes a target, it ceases to be a good measure.”
Academia has decided that the evaluation of merit should be based on the number of articles published, then supplemented by the number of references to those articles. That has been a force in stimulating papers production (there are also other reasons, like it is easier to write a paper, more opportunities to publish it, there are more people all over the world writing them …). Whatever the reason, the result is that we are drowning in information. This is where companies like Gartner make a living: sorting, distilling, and customising information to fit a specific need at a specific time.
The creation of information will not abate, it will only increase in the coming years. In a short while, machines will start creating “papers”, i.e. information, and machines will become the largest user community of information. Machines don’t go to conferences, nor subscribe to education courses. Most likely they don’t need peer-reviewed information since they have a way to review it by themselves. Additionally, machines are lighting fast so you can expect information to grow even more than today.
I am talking about machines, but it is obvious that the engine is artificial intelligence. AI natural language understanding, syntheses and creation has achieved an impressive level. Add to this a better than good translation capability, voice syntheses, image recognition and creation, meaning extraction and you have a perfect storm. The world of knowledge will not be the same by the end of this decade.
This will have profound impacts on education, on business, on the job market, even on the “meaning” of knowledge. I’ll tackle this in the next post.
