From Tennis Courts to Courtrooms: AI's Influence on Decision-Making
Navigating the fine line between human judgement and AI oversight.
Previously, on Giuseppe’s Glimpse: In the last episode, we looked at top brands’ strategies, highlighting the crucial role of trust in fostering lasting connections amidst market uncertainty. If you missed it, catch up here!
Hey there! 👋
Call it a bit of a mid-life cliché if you will, but lately, I've made it a habit to hit the tennis court with a friend whenever I can.
Now, I'm definitely not claiming to be the next Serena Williams or Roger Federer, but there's something about a good game of tennis that really gets me going.
The other day, I was in the middle of a heated match, when suddenly my opponent challenged a call. 🎾
Now, back in the day, if we were pros, it would've been up to the umpire’s judgement alone. But times have changed.
With the introduction of the Hawk-Eye system, which uses 6-10 cameras around the court to create a 3D map of the ball’s trajectory, we've moved beyond relying solely on human judgement. Pretty cool, huh?
So, what’s the big deal?
Well, I stumbled upon this fascinating piece from The Economist, shedding light on how AI oversight in these high-pressure situations is refining human performance.
David Almog, a behavioural economist at Northwestern University, has been digging into the dynamic between humans and AI, and tennis is like a gold mine of insights.
He found that, with Hawk-Eye keeping a watchful eye, tennis officials made 8% fewer errors. This improvement just goes to show how the fear of public correction can really sharpen our decision-making skills. 🔝
But, get this – there’s a twist: officials are now more inclined to let a close 'out' ball slide. It seems like the fear of public dissent has pushed line judges to give players the benefit of the doubt, probably to avoid a PR fiasco.
Will AI be the new ref?
This got me thinking about the role of technology in our lives, especially when it comes to decision-making.
It's becoming increasingly evident that AI is permeating not only our personal lives but also our professional ones.
And as its influence grows, it's set to shape our decision-making processes in ways we may not fully grasp yet.
Let’s take doctors, for example – the 'umpires' of healthcare. 🩺
For them, making error-free decisions is paramount. Yet, could the 'Hawk-Eye' of healthcare induce a similar shift in their judgement? And if so, at what cost?
Imagine a patient walks into their doctor’s office with some minor complaints. With AI throwing out a bunch of potential diagnoses, the doctor might feel the need to prescribe a bunch of meds just to cover all bases. But do they really need all those pills? It’s a slippery slope. 💊
And it’s not just medicine; law’s in the spotlight too.
Picture AI analysing legal cases and advising judges to play it safe, stick to the script, and keep things predictable. What would this mean for fairness and individual rights?
I’ll admit, it’s a bit unnerving, isn’t it?
Brains & Bytes: Joining forces for success
Sure, AI’s ability to crunch numbers and analyse data faster than any human ever could is a huge asset.
But all these scenarios also require something that goes beyond these skills: empathy, intuition, and the ability to think outside the box—all inherently human qualities. 🫂
They are what allow us to connect with others emotionally, tackle problems from unconventional angles, and devise innovative solutions that data alone might miss.
That's why we must tread carefully as we navigate this new era alongside AI.
While AI offers valuable insights and support, it shouldn't overshadow or replace our human judgement. Instead, it should complement our expertise, enhancing rather than supplanting it.
So, as we dive deeper into the wonders of technology, let's not forget the value of our own judgement and intuition. Together with AI, they drive us towards a brighter future. 💫
Let's continue this conversation. How do you see AI impacting decision-making in your field?
Stay curious! 🙌🏽
-gs
Oh, wow! You made it to the end. Click here to 👉 SHARE this issue with a friend if you found it valuable.
I think your provocation is based on an example that is not apples to apples.
So let me throw a provocation back.
An AI model for sport rules has a binary outcome: does the action fall into one case or another (in or out, for example). Training of the model is fairly simple because the variables are limited.
A medical model is most likely trained to highlight anomalies based on a much wider range of variables and requires ongoing interaction and validation by the doctor (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955430/).
The first provides an answer, the second accelerates a process.
Which makes the provocation on AI as a contributor vs. a sostitution a bit of a moot point.
Complete replacement of the human element is something that has a data availability problem, a data cataloguing problem, a tokenization problem, a model prioritization problem (LLMs? Diffusion? They all have pros and cons) and a tech availability problem (GPUs).
More than anything an interoperability problem. Private systems (the larger part, since public organization don't have the funding to develop AI systems that are just as powerful) won't be interoperative.
We will see an increasing closure of data as IP: private companies won't share their data with others and so a complete data lake of medical pathologies will most likely not be available - unless some international organization emerges.
Until all these elements - which are ultimately economical and not technological - will be solved, humans will still have a role.