The emergence of Artificial General intelligence (AGI) into the public consciousness is one of the big early developments of 2023.
AGI refers to a system or software able to display human cognitive abilities, which, just like humans, can generalise to unfamiliar situations.
However, unlike the AI we have today that focuses on augmenting or replacing humans by improving our effectiveness or efficiency, AGI is closer to the representation of AI that we see depicted in movies: robots displaying adaptation, learning, creativity, and perhaps even sentience.
Dall-E 2 and ChatGPT are among the most publicised current examples of AI. The former uses natural language to rapidly create realistic images or art from text descriptions, while the latter is a large language model designed as a chatbot to answer user questions in a conversational manner.
What are the limitations of AI?
I recently asked ChatGPT to reveal the biggest issues that could potentially influence the future of sport. It reasonably stated climate change, athlete safety, corruption, doping, inclusivity and overuse injuries.
Then I asked for the main catalysts required to reach new levels of human performance. It responded advanced physical and mental training techniques, new technology, and a better understanding of nutrition and genetics. A quick Google search might have given the same information. Concerns have been raised around bias in the system, its inability to appropriately source information, and perhaps most worryingly, its capacity to simply fabricate occurrences that never took place.
So, with the substantial limitations of existing AI, how far are we from actually achieving AGI? For some, it's just around the corner, for others, quite some way off. Almost daily banter occurs on social media between prominent AI researcher and author Gary Marcus and Meta's Chief AI Scientist, Yann LeCun. Marcus has continually called into question apparent progress in this space, whereas LeCun is considerably more bullish. Only time will tell who is right. For the record, I am firmly in Marcus's camp.
I don't think it matters for sport right now because there are plenty of gains to be made with what we have right now.
How will AI impact sport?
Despite its many limitations, AI is developing much faster than sport. In fact, it's not even a close-run race. That shouldn't be taken as a criticism of sport. It's simply inevitable given the resources being funnelled into AI, as well as the high ceiling on its potential gains. AI also has far fewer checks and balances to navigate, and a completely different level of risk tolerance.
I recently asked people on social media to comment on the opportunities they saw for AI in sport. Comments ranged from more efficient written communication, faster access to required knowledge, and even the design of visual tools to help athletes learn. The internet provides many ideas and recommendations for AI's incursion into just about every element of the sport experience, from new media platforms, to injury prediction and individualised training prescription.
While it's tempting to gravitate towards the latest and greatest developments in AI, doing this now in sport is largely destined to be nothing more than a fad. Sure, sport will always be a competitive environment, with rivalled organisations continually looking for ways to get the edge. But right now, sports are nowhere near fully realising the far more rudimentary, yet more impactful, benefits of existing AI.
For example, we could intentionally make large parts of many current sports roles redundant overnight through automation of low-level tasks. All sorts of reporting, communication, coding, and analysis remain as predominantly manual tasks. The opportunity to generate more time, freedom and creativity in our jobs is already before our eyes - we just need to take it.
Why the lack of gains?
Some organisations already leverage AI to make more accurate decisions and improve efficiency, but something as simple as cultural resistance may prevent others from taking up its opportunities. Ironically, time poorness is one of the biggest complaints I hear and observe from people working in sport. Other times, people are too busy to change processes, simply prefer the status quo, or still aren't aware of what is possible.
This unwillingness to use available technology for its most obvious and intended purpose is not new. The influential mathematician Merrill Flood talked about the benefits of computing to relieve us from mundane tasks and provide more time for creativity and social pursuits in the 1950s. I wonder what he'd think now?
The path towards AGI
If the day arrives when AGI eventuates, it would transform almost every industry. It is not something that sport needs to concern itself with now, because we need to walk before we can run. And it's probably just as well. Using AI requires the same thought, care and due diligence we give to any new method or technology before implementing it with our athletes.
- What does it mean for AI when using poor data to recommend signing a new player?
- Who is liable when AI makes a 'bad' decision to let an athlete compete and they are injured?
- Who is responsible in a sporting organisation to govern and update the AI?
These questions and more could dramatically alter how sports jobs look, and the skills we need to train for.
And they need satisfactory answers.
