Human beings love patterns. Whether it’s on an extensive or basic level, we always want structure and predictability to what is an unpredictable life. We follow a procedure to get us from A to Z, but that is no different to the lines of computer code which artificially intelligent robots have to follow. So, when Reform says 250,000 public sector jobs could be taken over by AI, you have to ask: is our love of structure and procedure – be it in the workplace or our social life – to blame?
In the report, the think tank says: “For many other roles, new technology will increase productivity. McKinsey estimates that 30 per cent of nurses’ activities could be automated, and a similar proportion for doctors in some specialities, enabling those skilled practitioners to focus on their non-automatable skills.”
The argument against this would be that people prefer to disclose information to another human rather than robots. The latter can only synthesise empathy and understanding.
It goes on to add: “Some technology will improve public-service delivery. Various companies aim to develop artificial intelligence that can diagnose conditions more accurately than humans. The UK should evaluate drones and facial-recognition technology as alternatives to current policing practice, while recognising concerns about the holding of people’s images.”
It’s wise for the report to take into account that robots storing personal data in computer code isn’t entirely safe. Aside from the rapport argument mentioned above, we can trust a human doctor to keep information and documents safe. Granted, some medical data may still be stored on a database which could be hacked (if the individual manages to break past the firewalls, encryption and any other protection in their way). One can only hypothesise, of course, but I consider it likely that AI in the medical profession could lead to an increase in loss.
In the last part of the segment of the report, it says: “Even the most complex roles stand to be automated. Twenty per cent of public-sector workers hold strategic, ‘cognitive’ roles. They will use data analytics to identify patterns – improving decision-making and allocating workers most efficiently.
“The NHS, for example, can focus on the highest-risk patients, reducing unnecessary hospital admissions. UK police and other emergency services are already using data to predict areas of greatest risk from burglary and fire.”
This is where the problem lies. How do we comprehend aspects of our lives? Data. Yet, when the calculations go beyond what the human mind is capable of, we use a calculator – a weird offspring of AI, as it were. Humanity compartmentalising aspects of our day-to-day lives offers both advantages and disadvantages: it provides us with understanding, but the only problem is that nowadays, the computer is doing the interpretation for us.