Amara's Law- "Overestimating the short-term and under-estimating the long-term impact" is not unusual. Take GPS
Starting in 1978, a constellation of 24 satellites (now 31 including spares) were placed in orbit. The goal of GPS was to allow precise delivery of munitions by the U.S. military. But the program was nearly canceled again and again in the 1980s. The first operational use for its intended purpose was in 1991 during Desert Storm; it took several more successes for the military to accept its utility.
Mistaken predictions lead to fears of things that are not going to happen.
Today GPS is in what Amara would call the long term, and the ways it is used were unimagined at first.
This important article from MIT shows how it will take longer and cost far more to effectively harness the benefits of AI. MIT state that unless an enterprise has successfully progressed its digital journey it will almost certainly fail to benefit from AI.
MIT list key barriers to success including:-
- Lack of clear AI strategy
- Lack of AI talent
- Functional silos constrain multiple AI applications
- Lack of leader's ownership & commitment
- Lack of technical infrastructure to support AI
- Lack of collected data
- Limited usefulness of data
- Lack of changes to frontline processes after AI's adoption
And remember that AI is only a part of the overall story. Even the manufacturer of the world's most AI enabled vehicles and manufacturing plants, TESLA, is still dependent on technology deployed in 1968 :-
Programmable Logic Controllers (PLCs).
These replaced electro-mechanical relays but still operate in a rigid and structured manner. It takes weeks for consultants to reconfigure these in the same way it takes weeks or longer to reconfigure insurer's core legacy systems. Robots are tied to this limitation.
This is one reason why it takes longer and costs more to plan and deploy AI then vendors pretend when hyping the benefits.
Nevertheless organisations need to square the circle and choose technology partners that deliver the digitisation journey and provide the digital platform for effective General Artificial Intelligence.
The report below shows the sins to avoid.
A lot of AI researchers and pundits imagine that the world is already digital, and that simply introducing new AI systems will immediately trickle down to operational changes in the field, in the supply chain, on the factory floor, in the design of products. Nothing could be further from the truth. Almost all innovations in robotics and AI take far, far, longer to be really widely deployed than people in the field and outside the field imagine.