【Press Release】Report on "AI x Sustainability x Open Innovation" Seminar - From case studies of agent functions in the real estate and education fields using autonomous AI to recommendations on how to use generative AI to address the issue of population decline

Press releaseEvent2023-07-07

Cover image for 【Press Release】Report on "AI x Sustainability x Open Innovation" Seminar - From case studies of agent functions in the real estate and education fields using autonomous AI to recommendations on how to use generative AI to address the issue of population decline

Recursive Co., Ltd. and eiicon Co., Ltd., which operates the open innovation platform "AUBA," held a seminar entitled "The Future as Discussed by Industry Leaders in AI × Sustainability × Open Innovation" on June 29, 2023 (Thursday). We will provide a digest of the contents of this seminar.

From left to right: Moderator Shun Wakabayashi, Tiago Ramalho, and Soichiro Murata. Takuya Kitagawa participated online.

The speakers were Takuya Kitagawa, co-founder and director of the public interest corporation Well-being for Planet Earth, Tiago Ramalho, who founded Recursive in Japan in 2020, and Soichiro Murata, a professional in open innovation. The talk session started with discussion on the usage of AI and open innovation, which is also a trend in the world, to create more powerful businesses by utilizing fields that do not have resources within their own company, as highlighted by recent investments by Microsoft in OpenAI.

Q1. In which fields is the utilization of generative AI already advanced?

First, Mr. Kitagawa introduced how AI functions as an agent in place of humans. He explained how autonomous AI services provided by the American AI startup company Adept can understand natural language and derive answers. Continuing with the example of searching for real estate properties, if one speaks specifically about the desired requirements to the AI, it will search the website, show the location of the property on the map, and clicking on the detailed link will display the properties that meet the criteria. He explained that support AI that navigates results not by answering in natural language, but by navigating websites through clicks and transitions has already started to function as an AI agent.

On the other hand, Mr. Ramalho explained that chatbots can answer questions for information that companies and governments disclose but are difficult for the general public to find, not just by creating text but also by generating text. He argues that this will make access to information more convenient and can achieve a transparent society. He also took education as an example of how AI functions as an agent, mentioning that generative AI can customize and provide appropriate questions for each student, which can enhance the learning effect, making it an area where generative AI can be expected to excel.

Regarding education, Mr. Kitagawa further explained that a Shogi program that analyzes the winning percentage was another example of AI functioning as an agent. The winning percentage changes every time a move is made, and even those who are not familiar with Shogi can understand the game situation and context, making spectator sports of Shogi interesting again. He proposed that AI could play a major role in the field of "education x entertainment" as it would make anything more interesting if the context is understood.

Q2. Challenges of generative AI

Mr. Ramalho said that the quality of the output is still a major challenge. Mr. Kitagawa mentioned that he has been given false answers by AI before, so reference checks and fact-checking of AI output are very important. Mr. Kitagawa continued saying that in the United States, ethical decision-making by AI and its ability to answer critical questions are being researched as challenges. The output of AI has a significant impact, as it can cause behavioral changes in people and can lead to good results in some cases, but it can also have the opposite effect. Therefore, it is a significant challenge to ensure the quality of AI output.

Q3. Challenges on the Japanese corporate side in open innovation/ Q4. How to solve these challenges

Mr. Murata explained that there are three challenges for Japanese companies. First, they are not good at making decisions to work with other companies. Second, while they use open innovation as a means, it is not clear what they want to achieve with other companies and what they will do to achieve it. For example, "working on DX" or the goals and objectives are unclear. Third, they do not have knowledge of new technology fields, so they often delegate projects to startup companies.

Regarding the differences between Japanese and American companies, Mr. Ramalho explained that in the United States, digital technology is regarded as the center and asset of business, and strategies are formulated by placing experts in that field. However, many Japanese companies do not have such an approach. Mr. Kitagawa explained that American employment is fluid, and people need to learn new things to survive. He also mentioned that employees' commitment is clear. Additionally, due to Japan's culture that values harmony, many cases spend time seeking consensus from many stakeholders for a single issue.

After hearing the explanations from Mr. Ramalho and Mr. Kitagawa, Mr. Murata proposed that Japanese companies should review their strengths and expertise and actively impart industry and product knowledge to startup companies to work together to create new things.

Q5. What can companies with technology do?

Mr. Ramalho said that companies without data can educate on how to collect and clean up data and how to overlay that data with solutions like generative AI to create value. He also touched on the fact that data is as important an asset as cash, but many companies do not realize that. He wants to support greater understanding of the importance of data.

Regarding open innovation, Mr. Kitagawa said it is essential to confirm what Japanese companies are expecting from it. For example, if it is ROI or an enterprise vision-based discussion. It is important to understand the needs and what kind of sense of satisfaction startups can provide to Japanese companies.

Q6. How should generative AI be used for a sustainable society?

Mr. Murata stated that it is essential to ask questions and learn basic things. Mr. Ramalho said that democratizing access to AI solutions is important, which will empower each individual, and he talked about the realization of a fair society where everyone has equal access. Mr. Kitagawa mentioned that when we think about sustainability, we often think about environmental issues, which are undoubtedly important, but he believes that it is possible to respond to the problem of declining population. He suggested that if there is a system that anyone can access, personal problems related to marriage and childbirth, such as financial concerns that prevent people from getting married, can be solved by a financial advisor system, and AI counselors can handle consultations such as infertility treatment. He proposed that such utilization of AI could solve individual problems.

After the seminar, participants expressed positive feedback, stating that they gained new perspectives and knowledge on AI utilization and heard advice that would be helpful for realizing open innovation. Some also expressed that the seminar allowed them to think positively about the future of AI utilization and coexistence.

As a multinational company with employees from 17 countries, Recursive will continue to report on global AI trends and related topics periodically.