“Stephen Hawking – will AI kill or save humankind” was the title of a blog post by Rory Cellan-Jones on BBC News. This was a report on a speech by Stephen Hawking at an event in Cambridge in October of last year at the opening of the Centre for the Future of Intelligence. Stephen Hawking summarized his speech by saying “"In short, the rise of powerful AI will be either the best, or the worst thing, ever to happen to humanity. We do not yet know which."
BBC News reported in January of this year that a Japanese Insurance firm will be laying off 34 staff and replacing them with an AI system that can calculate payouts. The firm expects to save 140m yen ($1.2m) a year in salaries after the 200m yen AI system is installed. The annual maintenance is expected to be 15m yen. The AI system is the IBM Watson, which is described as cognitive technology that will gather information needed for the policy holder’s payout by reading medical certificates and data on surgeries or hospital stays. By eliminating people with AI, the efficiency of calculating payout should increase by 30%. Saving salaries and being more efficient may be good for the insurance company, but I’m sure it does not feel good to the 34 staff who were replaced.
Hitachi AI technology/H takes a different approach to the use of AI and staff. Dr. Dinesh Chandrasekar, Director, Global Solutions and Innovation(GSI) Group at Hitachi Consulting, published an article on linkedin which showed how Hitachi AI Technology/H was used in an existing warehouse logistics solution to provide appropriate work orders based on an understanding of demand fluctuation and on-site kaizen activity derived from big data accumulated daily in corporate business systems, and its verification in logistics tasks by improving efficiency by 8%.
The key to the difference in Hitachi’s AI approach is the incorporation of Kaizen, which humanizes the workplace and solicits the participation of the workers in increasing productivity.
Dr. Chandrasekar, explains that conventional systems, operate on preprogrammed instructions and do not reflect on-site Kaizen activities or employee ingenuity. In order to reflect this input, a systems engineer may need to redesign the system, which could be disruptive and expensive. It may even require the rewrite of the work process and design which would make it difficult to respond to demand fluctuation and corresponding on-site changes. By taking a deep learning approach to AI and incorporating it into business systems, it will be possible to incorporate Kaizen activities or employee ideas while flexibly responding to changes in work conditions or demand fluctuations to realize efficient operations.
Other examples of the use of Hitachi AI Technology/H are shown in the following 5 min video. The above warehouse example about improving worker efficiency by 8% is shown. Another example shows the use of Hitachi AI Technology/H to enhance the buyer experience by locating staff in the optimum location in a retail store to increase sales by 15%. The operation costs of a desalination plant was decreased by 3.6%. and the power consumption costs of a high speed train was also decreased.
Instead of replacing staff, Hitachi AI Technology/H can improve the efficiency and productivity of human staff by incorporating Kaizen, the humanizing process of improvement. In this way AI can be lead to Social Innovation and save mankind.