The dark side of AI: ‘Everyone is simultaneously extremely motivated and extremely close to burning out’
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Progress and investment in AI have accelerated at an unprecedented pace in recent months, with companies of all sizes making it a priority, researchers jumping in to take their ideas to market, and consumer adoption through the roof.
But as the frenzy around AI goes into overdrive, the technology is not just disrupting industries. It’s starting to take a human toll too, a recent post and the response to it by Hugging Face machine learning scientist Nathan Lambert seems to suggest.
“Seeing all of the noise makes it very hard to keep one's head on straight and actually do the work,” Lambert wrote. “It seems like everyone is simultaneously extremely motivated and extremely close to burning out.”
Burnout is becoming increasingly common among AI professionals, said Manail Anis Ahmed , a technology ethics lecturer at Princeton University ’s School of Public and International Affairs and a LinkedIn Top Voice on artificial intelligence.
“The reason is that the hype cycle this time has gone frantically overboard,” said Ahmed. “This is the latest iteration of a transformative technology emerging – and people realize that they can’t just swat it away.”
AI advancements are rolling out at a rapid clip
AI has seen a meteoric rise over the past 12 to 18 months, fueled by research being released at a rapid clip and corporations deploying it even faster. There seems to be a new breakthrough every week, with investors pouring money into AI startups and players both big and small duking it out to unveil the latest notable advances.
Take, for example, the fact that it took OpenAI less than four months to roll out GPT4 after GPT3.5, the large-language model powering its ChatGPT. Or that it took the now-renowned generative chatbot a record-breaking two months to reach 100 million users.
“There’s a very strong go-to-market dynamic at play, which is leading to a sense of burnout,” said Abhishek Gupta , founder and principal researcher at the Montreal AI Ethics Institute .
“It hasn’t even reached fever pitch yet – people are still in a phase of exuberance due to the opportunities, attention and excitement of its potential.”
This is translating into a mad dash among both big tech companies and smaller startups. Google upped the ante by investing $300 million into Anthropic and unveiled its own AI chatbot Bard within days of Microsoft’s (LinkedIn's parent company) recent $10 billion investment into ChatGPT creator OpenAI. Meanwhile, smaller AI startups are constantly under the venture capital scanner to grow and scale their businesses.
“It’s frothy, predictions are hard to make, the space is moving, everyone is motivated to move fast and scared to be behind, it's exciting and tiring,” Yohann Abittan , a former AI product manager and now founding partner at VC firm Armada Builders , commented on Lambert’s LinkedIn post.
AI ethics is even more complicated
The issue is even more pronounced among those on the frontlines of trying to ensure ethical applications of AI, as MIT Technology Review reported late last year.
Professionals working on responsible AI or ethics are tasked with everything from developing responsible strategies and policies to mitigate harmful applications, like algorithms that spread hate speech or graphic images and language. They confront toxic content day in and day out, which AI systems only end up exacerbating due to the nature of how they run.
This isn’t entirely a new phenomenon, Ahmed pointed out. Social media content moderators have had to contend with harmful content for a long time, she said, with little to no regulation around those business models. That has just been compounded by AI.
“Now the can of worms is so large, we have to worry about a lot more, like prediction systems and algorithmic decision-making,” she said.
Teams who work on responsible AI and AI ethics also constantly face an uphill battle, said Gupta. They must evaluate and mitigate any potential harms before products are released, while everyone around them clamors for that to happen fast and “wants to play with the shiny toy,” he said.
“The successes are always silent – it’s a thankless job,” he said. “The only sign that you’re doing your job well is if something bad doesn’t happen. But if something goes wrong, it’s squarely on you.”
Ultimately, this can leave such professionals feeling overwhelmed and undervalued, causing their mental health to nosedive and leading to burnout.
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How AI professionals are managing burnout
In his post, Lambert offers a Ted Lasso quote as one way of dealing with burnout.
“Be a goldfish,” he wrote. “When things are moving so fast, it's good to remember that sometimes you'll waste a lot of effort or get scooped. The best thing you can do is to just accept it and keep going on with your process. You're not alone in this one.”
Others have shared general wellbeing tips that have helped them manage burnout. Former DeepMind engineer Aleksa Gordić , for example, underscores the importance of structure, drawing healthy boundaries and learning how to say no.
The responsibility doesn’t lie with individuals only, said Chris Mann , who wrote how companies and their leadership “need to be vigilant in helping our people manage their work, stress, and balance.”
Ultimately, it can help to find meaning and purpose in the work that you’re doing – without getting caught up in the rat race, said Gupta.
“You have to make an explicit choice and make sure, for example, that 50% of your tasks are aligned with that bigger purpose,” he said.
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Retired Principal at Braun and Steidl Architects
1ySt. Thomas' College of Engineering & Technology 122
CEO SolarGreenSavings.com accelerating the green energy transition through solar energy awareness.
1yUndeniable✅
Chief Product / Technology Officer, AstraQ | Building Multi Modal Agentic Workflows | Gen AI Startup
1yTanya: You are spot on. This time there is going to be huge transformation and old players getting replaced by new players who may not even be in business today. That excitement is making everyone want to put huge amount of hours and its hard to catchup with so much going in 100 different directions resulting in fatigue. Fear of missing the boat. Frequent AI break is recommended :-)
Systems Programming Consultant
1yLOL. Nothing like marketing hype to lead to burnout There are no intelligent machines. We only have the normal language abuse of referring to algorithms as intelligent. This is definitely an area full of bullshit. Proof? You can’t even define intelligence let alone a system that possesses such a trait. All you have are a bunch of excuses why failure should now be considered success