The world of AI research is in shambles. From the academics prioritizing easy-to-monetize schemes over breaking novel ground, to the Silicon Valley elite using the threat of job loss to encourage corporate-friendly hypotheses, the system is a broken mess.
And Google deserves a lion’s share of the blame.
There were approximately 85,000 research papers published globally on the subject of AI/ML in the year 2000. Fast-forward to 2021 and there were nearly twice as many published in the US alone.
To say there’s been an explosion in the field would be a massive understatement. This influx of researchers and new ideas has led to deep learning becoming one of the world’s most important technologies.
Between 2014 and 2021 big tech all but abandoned its “web first” and “mobile first” principles to adopt “AI first” strategies.
Now, in 2022, AI developers and researchers are in higher demand (and command more salary) than nearly any other jobs in tech outside of the C-suite.
But this sort of unfettered growth also has a dark side. In the scramble to meet the market demand for deep learning-based products and services, the field’s become as cutthroat and fickle as professional sports.
In the past few years, we’ve seen the the “GANfather,” Ian Goodfellow, jump ship from Google to Apple, Timnit Gebru and others get fired from Google for dissenting opinions on the efficacy of research, and a virtual torrent of dubious AI papers manage to somehow clear peer-review.
The flood of talent that arrived in the wake of the deep learning
explosion also brought a mudslide of bad research, fraud, and corporate
greed along with it....<<<Read More>>>..