By Steven Orpwood

July 2023

 

A story attributed, although unsubstantiated, to Margaret Mead, an anthropologist, says that the earliest indication of civilisation was not pots, tools or religious artifacts, but a broken femur that had been set 15,000 years earlier. Whether true or not, it’s interesting to consider that such a broken bone renders the sufferer unable to walk, defend themselves or contribute to a group. As such, earlier, fiercer tribes would have been more likely to leave or despatch the afflicted. What the healed bone suggests is that at some point, human attachment, usefulness and caring superseded the desire of the carer to singularly preserve their own life.

 

As time has passed, humans have become better at caring for those with broken bones, we have specialists to assess and treat them, hospitals to care for them if the injury is life-threatening, family and friends to provide basic needs if hospitalisation is not required, and technology to allow movement and the continuance of a normal life as simple as possible.

 

Human intelligence has taken a problem and solved it. We have preserved life, created new roles to heal and provide care, food, and water provision through primary and secondary industries, and even the ability via the fourth industrial revolution (or fifth depending on your interpretation), to allow people to work from home, via the internet, and information technologies. Originally, the most efficient way to deal with the broken femur was elimination of the person; caring for the patient was less efficient, but over time we have made the process efficient again and everyone benefits.

 

Similarly, pharmaceutical development has long been a haphazard affair. Alexander Fleming discovered penicillin by going for a two-week holiday and finding on his return that the mould on a contaminated sample had reduced bacterial growth. The formalisation of drug development and increasing use of statistical models, plus new technologies, has made drug development more efficient. For both bone setting and drug development the process has become more streamlined, but the number of people involved in those industries has increased, to the point where both are major employers.

 

In recent times, researchers at McMaster University and MIT have discovered a new antibiotic, Abaucin, that can be used to kill a hospital superbug. They used an AI algorithm to screen data detailing different chemicals’ ability to kill bacteria to identify if said chemicals had antibacterial qualities or not. Approximately seven thousand compounds were tested which revealed a shortlist of 240, in one and a half hours, which were laboratory tested producing a final shortlist of nine. It’s important to note that whilst the AI could process many more records than a human team, and could produce a shortlist significantly faster, making the process much more efficient, there were still roles for the scientists to complete final testing and determine the efficacy, applicability, and safety of those drugs.

 

In all the cases above we move from one stage to the next, which may at first complicate matters and make things less efficient. In time though, these new ideas generate new possibilities and activities, all requiring people to fill roles. The consequence being more, not less, employment, and because the overall process is more efficient, it results in better outcomes, with cheaper costs than before. AI is not the end, it is not a job destroyer, but an opportunity to improve, to create more roles and new avenues of progress. Join Aim in celebrating AI and using it in our products to provide better service to our clients, allowing them to use their human capital to gain an advantage over their competitors.

 

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