Ahead of the release of the new bookThe Magic Conveyor Belt: Supply Chains, AI, and the Future of WorkDr. Yossi Sheffi, Director of the Center for Transportation and Logistics at MIT, discusses the application of artificial intelligence in global business, how leaders will implement this technology, how governments will regulate it, and how workers will face the challenges of rapid change. Discuss how to protect life inside. change workplace.
Dr. Yossi Sheffi has authored numerous books on supply chain management, technological advances in global business, and most recently the impact of artificial intelligence on how businesses operate. Beyond academia, he has founded and sold logistics, SCM, and business consulting firms, and his resilience, from supply chain to talent, can give companies a competitive edge in the midst of a global crisis. I have consistently argued that it can be done.
We asked him about the likely growing role of AI in global business and how stakeholders might prepare for what could be called a technological revolution, and how this could lead to mass employment in the future. Ask what it means.
Supply chain and AI
We started by asking Dr. Sheffi what companies can gain by introducing AI into their supply chains. He is optimistic about the transformative impact of higher forecasting accuracy.
There’s a lot of work on risk management in general and we’re trying to find out what’s going on with all our suppliers. Because when you look at the financial data, you’re looking backwards. A quarter late.
If you want to know what’s happening now and in the future, media and social networks are a very good source of information from which you can mine data. It’s not just numbers, it’s text, photos, videos, anything we can find. Please understand all this.
Dr. Sheffi points out that perhaps the most promising application of artificial intelligence in global supply chains is its propensity to predict the outcome of decisions made at every layer of the network. The predictive capabilities of AI, which once employed teams of analysts, have the potential to breathe dynamism into a stagnant industry. Leverage previously underutilized data, such as social media and internet usage, to drive business decisions.
implication
Dr. Sheffy was ultimately optimistic about the implementation of artificial intelligence in general. However, regarding the potential risks, he said:
First, looking back at a lot of technology, this was just the feeling of the population. Back when computers, especially his PCs, were just coming out, there was a joke that every manufacturing plant had a man and a dog. The man comes here to look over the equipment and the dog keeps the man from touching anything.
The difference is today. Businesses are fully aware of the danger and are working on it. They already have guidelines in place.
This reaction epitomizes Dr. Sheffi’s inclusive attitude to the looming technological revolution. He frequently presents his AI within the historical context of the Industrial Revolution. Examples include Henry Ford’s implementation of the production line and the invention of the Internet. Such comparisons are compelling and suggest predictability that reassures both workers and businesses. But there are risks in relying on patterns that fail to consider the changing landscape of global business and the conflicting priorities of nations trying to regulate this technology. Of this unpredictability, Dr. Sheffi simply states:
And you get what are called new traits that the algorithm itself creates – the designers never foresaw or imagined this would happen.
AI development has accelerated exponentially in the past year, and it’s hard to say exactly what the near future will look like. This unpredictability has recently gained some prominent opponents, including the so-called “godfather of AI” Geoffrey Hinton, who has publicly expressed concern about the rate of change of the technology.
How should employees prepare?
The biggest fear felt among workers around the world is the impact this technology will have on mass employment. Dr. Sheffy approaches the issue with the same historically-oriented optimism. he said:
In the late 1970s and early 80s, ATMs became widespread in the United States. At that time, there were a total of 300,000 tellers in the United States. Do you know how many there are now? Over 600,000. why?
ATMs have made it cheaper to open bank branches. More jobs were created than were lost.
In our globalized world, any change in technology represents the potential to affect millions, if not billions, of individuals. Given that the nature of global supply chains requires a myriad of tributaries that are difficult, if not impossible, to track and predict, we must remain skeptical that AI will follow the same pattern. The problem here is not in the inherent nature of AI, but in its haste to be implemented in a very different context than ATM. On this, Dr. Sheffy agrees, stating:
I hope we don’t repeat the mistakes we made with globalization. Globalization has been great. On average it was great for people. People made money and, especially in the affluent world, the standard of living for the average person rose. Europe, America, Japan, China. But quite a few people are left behind.
A lot of manufacturing jobs went to China, both in the UK and in Europe and in us, people lost their jobs and communities suffered. What didn’t we do then? We didn’t realize it was happening until we got pretty deep into the process.
This raises the last question we had for Dr. Sheffy: How will governments react to seeing that they are being given the opportunity to regulate this early in their journey to technology? should?
how do you regulate?
The final piece of this puzzle is ultimately: Now that this technology has evolved to and continues to be widely applicable, what should states do to regulate it and protect workers and businesses? Dr. made an interesting point.
The strictest regulations are in China. China controls training data. Train only on specific data. It’s tied to your training data, so there’s no digression. However, this is a very extreme restriction of doing it at the input, not at the output.
China’s solution to restricting AI’s access to data and clarifying its capabilities is a noteworthy approach that has been successful on several fronts. Of course, China’s approach to regulation has authoritarian governance in mind, with questionable moral consequences (such as social scoring). The unintended consequences are perhaps like future-oriented regulations that should also be implemented in other contexts (limiting the distribution of deep fakes, for example, is arguably a forward-looking ambition). While the US, UK and others are undoubtedly focused on an “AI arms race” where wealth accumulation is the ultimate goal, China has very different priorities to enable rapid regulation. Of course, not all of these are consistent with democratic values, but the benefits of regulation should still be considered.
But how should governments respond to the need for millions of workers to reskill once the introduction has taken place?
We must start now to make sure those who have to change jobs have options…the government simply needs to buy their time [to allow workers to re-skill].
So, basically, it’s up to the state to take care of this new technology and invest the huge sums of money it can generate in workers who have lost their jobs. Retraining programs will shift workers from their current industries to focus on new areas of work created by AI.
my view
Supply chains have been a hot topic since the pandemic, with their future in question amid global shortages. Dr. Yossi Sheffi presents a future where AI is used to strengthen the strength of his global supply chain, significantly improve efficiency and make more accurate predictions. But be careful when bright prospects depend on a myriad of agents making the right decisions.
I do not believe that AI is prone to some sort of “disruption” in terms of global employment. Good practice of his leader in business as well as around the world.
