The world of AI research is in shambles.
And Google deserves a lions share of the blame.
Fast-forward to 2021 and there were nearly twice as many published in the US alone.
To say theres been an explosion in the field would be a massive understatement.
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But this sort of unfettered growth also has a dark side.
At the top, Googles shown its willingness to hire the worlds most talented researchers.
Just a few months later it fired another member of the team, Margaret Mitchell.
Its now barely over a year later and history is repeating itself.
The mudslide effect
At the top, this means the competition for high-paying jobs is fierce.
And the hunt for the next talented researcher or developer begins earlier than ever.
A quick Google Scholar search for natural language processing, for example, shows nearly a million hits.
Many of the papers listed have hundreds or thousands of citations.
Unfortunately, a significant portion of AI and ML research is either intentionally fraudulent or full of bad science.
What may have worked well in the past is quickly becoming a potentially outdated mode of communicating research.
The Guardians Stuart Richie recently pennedan articlewondering if we should do away with research papers altogether.
According to them, sciences problems are baked in pretty deep:
This system comes with big problems.
This drastically distorts our view of what really went on.
The PPS uses automation to flag papers containing potentially problematic code, math, or verbiage.
But the jobs likely too big for a handful of humans to do in their spare time.
According to areportfrom Spectrum News, there are a lot of problematic papers out there.
Most papers containing tortured phrases seem to come from the fields of machine learning,artificial intelligenceand engineering.
And were certainly not trying to imply that everyone studying AI is just out to make a quick buck.
But the systems set up to encourage the monetization of algorithms first, and to further the field second.
Currently, there is no widely recognized third-party verification authority for papers.
The peer-review system is more like an honor code than a set of agreed-upon principles followed by institutions.
