Written by Fola Yahaya
Obi, my eight-year-old son, was diagnosed with Type 1 diabetes at the height of the Covid pandemic almost three years ago. Covid hysteria meant his initial hospitalisation was even more traumatic than usual. The poor kid was stuck in an isolation ward, subjected to daily Covid swabs being shoved up his nose, and having his fingertips lacerated for two-hourly blood tests.
Out of hospital, we were bombarded with information on how to use insulin to keep him alive. This involved manual finger pricks at least five or six times a day, and looking up the amount of carbs before every meal to work out how much insulin to administer (not to forget working out what ‘correction’ dose to give him when we’d screwed up our calcs).
On average, this meant he was like a human pin cushion that was injected six or seven times a day. Yet despite this initial trauma, and having to explain for the umpteenth time that his diabetes is not the result of/fixable by changing his diet, he’s lucky.
Because of advances in tech, he now wears a battery-sized continuous glucose monitor (CGM) that lets me see his blood sugar on my phone and alerts me if he’s too high or too low. This has revolutionised diabetic monitoring, and he’s now on the waitlist for a small tubeless pump that will talk to his CGM and automatically administer microdoses of insulin to keep his blood sugar ‘within range’.
Now all we need to help him live a normal life is to let AI loose on a massive set of clinical data on how people respond to insulin, and computer vision to automatically calculate the carbs on our plates. This will help us achieve the ultimate goal, a pump or artificial pancreas that automatically adjusts insulin levels without human intervention. For all diabetics, AI can’t come fast enough.
Everyone I know, from the woman who cleans my office (who used ChatGPT to draft a letter that stopped her getting evicted from her social housing) to a derivatives trader I play squash with, is using ChatGPT on a daily basis. This poses the question: What would you do if it disappeared? Of course we’d all be fine, but as AI becomes as integral in (some) of our (Western) lives as electricity, it begs another question: What will we all do if it gets switched off? If you’re starting to worry, then perhaps it’s a sign you’re becoming ChatGPT-dependent. See how many of the below apply to you:
Seven signs you’re addicted to ChatGPT:
The holidays are a tricky time for any family. The novelty of hanging out with your kids wears off after a few days, and parents desperately Google/ChatGPT what they hell they should be doing to avoid a family breakdown. The more organised of us arrange activities in advance, with coding camps being a firm favourite of ambitious parents looking to secure their retirement by raising the next Elon Musk. However, I always thought coding camps were a massive waste of money and I saw an interesting note from a senior analyst at UBS who seems to agree with me.
Paul Donovan sees teaching kids to code and general science, technology, engineering and maths (STEM) education as a ‘stranded asset’, or something you’ve invested in that won’t give you a return. I disagree on the importance of STEM education, but I do agree on the critical importance of teaching our kids economics ;-).
I had a lot of fun testing my staff’s ability to tell AI-generated images from real ones this week. Happily, the outcome of the poll was a tie 🙂 which proved my point that AI-generated photos are now good enough to supplant stock images. This essentially kills the business model of Getty Images, Alamy and all the other huge stock libraries that have grown fat on our need for visuals.
For me, this is also another example (like the need for instant and cheap multilingual content) of big tech finding a solution to the insatiable desire for cheap visuals. From Instagram to YouTube, we live in an increasingly digital and visually-driven world. This demands a constant flow of images, which Getty and others used to supply expensively.
I’m not entirely sad about their demise (disclaimer: Getty aggressively came after me for using one of their images on a student website 30 years ago) but it’s already having a huge impact on the livelihoods of photographers, who serve a vital purpose.
However, there’s still a huge space for authentic, visual storytelling involving real people. Though this ‘reportage’ style footage will be replicable by AI, few brands will want to run the risk of being caught out by fake imagery, so I see the need for ‘real’ images only growing.
Aside from mass disinformation, AI is having a seismic impact on fraud. It’s rare that companies ‘fess up to being hoodwinked’ but here’s an interesting story about how a finance worker in Hong Kong was duped into paying US$25m by fraudsters posing as his company’s London-based chief financial officer on a video call using deepfake technology.
By the time you get this, our team will be in Cannes (6.50am flight from London!) for the World AI Cannes Festival. We’ll be reporting back next week on our key findings and stuff you should know. Until then, have a great week(end) and remember… lean in.
Generating great images: Here’s a great guide on how to use Midjourney, the best tool on the market for creating realistic images.
Using Perplexity for fact-checking: I’ve recommended this AI-powered search engine a few times now, but it really excels at fact-checking. Next time you’re writing something that demands factual accuracy, try asking Perplexity to fact-check your content.
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