Zero Is Larger Than Negative

 IT companies such as Microsoft and Amazon recently announced job cuts, claiming the cause to be Artificial Intelligence. However, I believe it is merely their technical advertising strategy to promote their AI-related products. Don't panic, as I don't think AI can really replace that many jobs in the foreseeable future.

I can still clearly remember that during my presentation at an international conference on video surveillance in 2012, a representative from a UK-based company told me that their company had spent quite a lot to investigate automatic video event detection systems. However, they later found out that all the methods proposed in recent publications were rubbish, as none of them could really be used in the real world. I felt embarrassed and changed my research direction after returning to Australia. I examined publications in this field and found that a lot of papers did not have any quantitative evaluations, and the sizes of the datasets were far from enough.

On a Sunday afternoon, I came to the lab at our university to study. My classmate from Sri Lanka said, "You are an excellent student. But it is a pity that you're supervised by Dr. Simon Denman. If you had the opportunity to work with Professor Simon Lucey, I believe you could have much more high-quality publications."

"No," I said, "I'm more fortunate to be guided by Simon Denman." Then I continued, "Simon Lucey's papers look good, but I don't like his style of research. He always first has an idea built on a tough mathematical foundation, and then asks students to do the development and experiments."

"So what's the problem?" my classmate asked.

"The problem is he gives his students too much pressure. They have to have good-looking results, otherwise, they will be blamed because the papers cannot be published in top venues," I said.

"But I'm still confused. What is the problem with that?" he asked.

"I believe research is full of uncertainties," I said, "as we are exploring an uncertain world." Then I continued, "I believe we should have at least some degree of freedom to adjust the methodology during the process."

A few years later, I was in Shenzhen undertaking a research project for Wi-Fi sensing, which means detecting human activities using information from communication channels. I resigned and left Shenzhen without any publications a couple of years later. I am proud of this, as no papers mean the best outcome. This is because zero is always larger than negative.

For all existing papers in this area, the arguments are contradictory. They all argued that using Wi-Fi signals was motivated by the fact that they could resist occlusion and even go through walls, while they hadn't explained how they prevented the influence of activities outside the room of the experiments.

The same problem exists in process mining. To evaluate whether a business process model is fine or not, researchers usually interview business users and directly ask them for verification. But how do we know they are not lying?

If the research outcomes of AI are not objective or true, why are we so scared of its influence in the current era? The spring of AI has yet to come.