💥 AI will affect 44% of ALL jobs by 2026!

+ AI loses to radiologists 😬

Matt V
October 04, 2023

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Here’s everything you need to know about AI today in 5 minutes.
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TODAY IN MINDSTREAM:

💥 AI will affect 40% of jobs within 3 years!
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🔨 Tool of the Week
😬 AI loses to radiologists
💡 AI-nspirational quote of the day
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💥 AI WILL AFFECT 44% OF JOBS WITHIN 3 YEARS

Financial top dogs Morgan Stanley have forecast that AI will impact 44% of all jobs within just 3 years.

It’s a startling figure, when you consider how AI entered the public conscience less than a year ago with the public release of ChatGPT.

It’s alllll gonna change.

Analyst Brian Nowak estimates that the AI technology will have a $4.1 trillion economic effect on the labour force — or affect about 44% of labour — over the next few years by changing input costs, automating tasks and shifting the ways companies obtain, process and analyse information.

If you were sleeping on the impact of AI, it’s time to wake up. It’s about to change everything, especially the way we work.

Morgan Stanley is also predicting that 5% of that $4.1T figure will be directed into software companies, who can expect to benefit big time from the AI boom.

If you weren’t, it’s time to start taking AI seriously!

Do you think 44% of jobs will be affected by AI inside 3 years?

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😬 AI LOSES TO RADIOLOGISTS

We usually report how AI is transforming the medical sector, but today we have a story that is hopefully an outlier!

In a new study, AI was unable to compete with seasoned radiologists on diagnosing lung diseases, failing to diagnose at the same level of accuracy as the doctors.

In the study in question, Danish researchers took a pool of 72 radiologists and four commercial AI tools and stacked them against each other to interpret 2,040 adult chest X-rays.

About a third of the X-rays displayed at least one of three diagnosable conditions: airspace disease, pneumothorax (collapsed lung), or pleural effusion.

Researchers report that AI tools were reasonably sensitive, diagnosing airspace disease 72% to 91% of the time among positive cases, 63% to 90% of the time for pneumothorax, and 62% to 95% of the time for pleural effusion.

However, researchers said these AI tools also produced a high number of false positives, with their accuracy lessening the more complicated the diagnosis became.

For pneumothorax, for instance, when these false positives were added up, the positive predictive values for AI systems were between 56% and 86%. Radiologists, on the other hand, got it right 96% of the time.

In other words, the radiologists were far better at finding and diagnosing correctly.

It’s not a disaster though. It still shows AI has potential to assist in diagnosis, and nobody is suggesting that AI replaces actual human intervention.