I agree with the fundamental thinking behind Data Free Flow with Trust. But as far as I can see, the “Data Free Flow” as referred to by Japanese businesses today, simply looks like an idea to “make money with the data we have.” Of course, a business must seek profit, but I think the value of data is far greater. But it feels like that even if they talk about Free Flow, businesses are much more interested in hogging data for their sole benefit.

I think we should separate information from short-term profit when we think about this. The business model, in principle, should not be about immediate profit but the possession of data allowing businesses to accurately analyze the market trend from which they offer new services and tools to other businesses and organization where they can collect more data. Unless this is the case, the conversation will always be around, “We have information others don't so let's take advantage of that in our marketing.”

Yes, for example, data from human behavior is extremely useful. Take a windshield wiper on a car. I know that some cars have the auto-operation mode but when a driver is required to do this manually, we can gather this behavioral data and measure the rainfall in a particular location in line with how humans sense rainfall. In fact, a taxi company did a test in this field and have mapped out the shape of rain clouds. So behavioral data can be of significant use in situations we never even thought about. But it's pointless if only one car manufacturer carried out such tests and hogged all the data. This is why I believe that we should look at data as a public asset.

I think there are two ways to look at this. One, is, as you say, we won't need as many people to do the jobs that exist today. This is particularly true for intellectual workers in general.

I think it's highly likely, particularly for administrative jobs. One local government tested out RPA(robotics process automation) to see how much of the workload at their city government can be automated. The result was over 90%. More and more, we will come to terms with the fact that some work do not have to be carried out by humans. It could happen to even highly specialized professions such as lawyers and doctors. But on the other hand, there will also be interesting developments. For example, I think the very concept of lawyers will also begin to broaden as we move forward.

One of the tasks for a lawyer is to do a research on past cases. Once AI comes in to help with the analysis of the case database, in an extreme sense, the quality sought in a lawyer may not be about having the smarts to cram the Book of Six Major Laws to pass the bar exam but an inherent ability to coordinate and build consensus.

Yes, I think a case similar to law will also apply to medicine. Two years ago, I had a general health check-up at this university hospital. There, I was told that they cannot provide me with accurate diagnosis because I have not been to this hospital in the last two years. What this means is the diagnostic precision is reliant on the availability of consistent data over time across medical agencies. It tells us how critical data is in a medical diagnosis. But if we look at this from another angle, it will become possible for more people to provide simple measurements and diagnosis if you have the necessary training, access to a medical database, and are assisted by AI.

If the personal medical data is shared with the family and the family gains access to medical database, let's say your grandpa suddenly collapsed at the house. The grandchild, with a help of technology, may be able to assess the severity of the situation and provide immediate emergency care of some kind.

In that sense, it is vital that we utilize data correctly. Using data to inform the allergens in food to someone with allergies is important and I think we should be doing this immediately. It's a mechanism that allows you to identify any allergens in the food at a store or a restaurant just by hovering a smartphone over it.

However, given how legal articles and cases are public data and medical data, private, we can't have anyone and everyone have free exchange of data. We must be absolutely careful about how to manage this.

The more a task becomes data-driven, the less an organization requires a labor-intensive work force. Because it frees them from a physical location of the office, I believe an organization will become more dispersed. Also work that physically carries out an instruction of another will become increasingly replaced by automation with data and computers. With such changes as a backdrop, companies will increasingly become a place to satisfy the need for self-realization such as a ‘mission’ or ‘to be the kind of person I want to be.’ I imagine that it will become a place where people come together for a certain mission. I will go out on a limb to say that companies will increasingly become something like an NPO. Of course, such transition won't be immediate, but I think such direction is already emerging in the expectations that young people today have for companies. The way data will be utilized in the workplace and how performance is evaluated will be based on how the organization supports this self-realization.

There are levels for data reliability. If the data generated from a sensor, there is a need to guarantee that the device operates properly. This requires some sort of a mechanism or a social infrastructure that will warrant the reliability of that device. For this, a mechanism is currently being devised where the sensors will carry a digital signature function and generate digitally signed data. In addition, there needs to be a mechanism where the provider of that sensor is held accountable for its safe operation. On the other hand, there are data that people generate and how to verify the reliability and credibility of such, particularly text-based data on social network is an extremely difficult issue.

Yes, for example, let's say one of the sensors are hacked and someone pretends to be that sensor and distributes fake information. We need to guarantee the reliability of the sensor data generated prior to the hacking. Having the record of viable digitally signed data from the past is the inherent function of blockchain so that's where it becomes useful. The guaranteed validity of digitally signed data is as important for past data. As we have seen, data reliability has impact on human lives so it's essential that such mechanism be reliable both technically and systematically or you cannot trust your life to an automated system.

It is important that the government takes the initiative to use the digital signature to guarantee that past data be correctly stored and that when a citizen requires disclosure that the correctly stored information is properly disclosed. There also needs to be a robust and transparent data governance to properly store and maintain data. However, even before the technical consideration, it is critical that all of us have the right mindset about the importance of data.