Be Careful What You Wish For: AI And The Cult Of Productivity
Dvorah Graeser
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New advances in artificial intelligence (AI) are paving the way towards increased productivity. However, as we harness this potential to enhance efficiency, we have to ask whether our current measures of productivity are truly representative of the work that we desire and value. The pervasive culture of immediate response to electronic communications such as emails and Slack messages has come to symbolize productivity. Yet, this ostensible achievement could potentially undermine our capacity for profound, concentrated work.
Calvin Newport, in his seminal book "Deep Work", elucidates the concept of deep work as a state of distraction-free concentration that allows the human brain to operate at its highest level (see link 1 below). It is a mode of work that fosters innovation, creativity, and problem-solving. With the advent of AI, the balancing act between enhancing productivity through technology and maintaining the potential for deep work becomes more difficult.
In a recent interview, Prof. Newport described the problems of rapidly switching between different messaging systems – and even worse, between Slack/email and social media apps (link 2). Each time we switch, we have to pull our brains away from the old task, and push our brains into the new task. ?All of this pushing and pulling wastes a lot of mental energy. Ultimately we become so tired and distracted that we are unable to do any deep work. Apparently the situation has become so bad that Microsoft workers reported that they routinely had to work in the evenings, after their official work day was done – just to complete any meaningful work.
The culprit in the case of the Microsoft workers was said to be video meetings – but it could be Slack, or email, or any of the many other communication apps that are supposedly “productivity enhancing”. They increase the speed of certain tasks, like group conversations. It means that many group dependent outputs are in turn reliant on fast, repeated group chats – rather than a single weekly meeting, say.
And as Prof. Newport pointed out, if you’re the only one in the organization not quickly responding on these apps – you become the problem. You hold everyone else up and prevent the group’s work from being completed.
Deep work, on the other hand, requires hours of concentration and focus – without switching every few minutes to a new task. I personally find that I have to remove distractions to do any deep work – putting away my phone, turning off various app notifications on my computer, and even putting in earplugs to reduce ambient noise. Plus it takes time for me to settle into a deep work task, so I have to allow enough time for that process also.
Some AI productivity tools do seem to be compatible with deep work. After all, who wants to transcribe audio when Otter is available (link 3)? Grammarly can be helpful for spelling and grammar, especially for non-native writers in a language (link 4). It now claims to also help with style and tone. Tools like Otter and Grammarly help you – but they don’t claim to do the work for you.
I’m less sanguine about tools like Dreamstudio (link 5), Lexica.art (link 6) and Craiyon (link 7), which create images based on text prompts. Full disclosure: I use Lexica.art and Craiyon, and will probably try other such tools for creating illustrations (although this week I went old school with Unsplash). This is because I am completely art and visual image challenged. I can write a piece, but illustrating it? I never graduated beyond stick figures. ?So why am I actually a bit worried about these tools? First, because they were trained by scraping works by real artists, which may not be legal, according to recent copyright court cases (links 8 and 9).
Second, generative AI tools for creating illustrations – or text for that matter – raise many questions about the ultimate value of the work. As brainstorming tools, I find them really helpful – particularly ChatGPT (just don’t rely on it for any facts, link 10). But in its current state, generative AI couldn’t come up with the Deep Work book, or even the concept of Deep Work. In seeking quick productivity solutions, are we cheating ourselves of the possibility of producing truly excellent work?
AI helps productivity or kills human deep work – what do you think? Comment below, and?schedule a meeting with me ?to go more in depth about any questions that you have about AI supported innovation.
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References
1.??????The original blog post announcing Deep Work: https://calnewport.com/deep-work-rules-for-focused-success-in-a-distracted-world/
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3.??????https://otter.ai/
4.??????https://www.grammarly.com/
5.??????https://dreamstudio.ai/
6.??????https://lexica.art/
7.??????https://www.craiyon.com/
11.??Interested in more work by Cal Newport? He has a website with videos on Deep Work https://www.thedeeplife.com/
Photo by Sonja Langford on Unsplash
Founder and Creator of Brand Therapy | Brand Strategy, Innovation Adoption, and Market Alignment Expert
1 年Digital transformation tools have proven distracting. But web3 tools are capable of speaking human (AI conversation vs computer io, immersive spaces vs 2d screens) and therefore capable of doing what no tools have before, augmenting our human capabilities of communication, empathy, and concentration rather than distracting our fragile attentions. That’s why companies like TeamFlow.Institute are forming to make sure AI doesn’t replace even more humans with automation, but allow teams to do what only the most disciplined of humans can do on their own, achieve team flow.