IWCIA2021 | Keynote Talk
2021 IEEE 12th International Workshop on Computational Intelligence and Applications November 6-7, 2021 Hiroshima City, Japan
going VIRTUAL!!
GENERAL
- IEEE IWCIA2021 TOP Page
- Call for papers
- Important Dates
[update:7/19] - Venue and Conference Map
- Organizing Committee
- Contact
PROGRAM
- Technical Program
[update: 10/21] - Keynote Talk
[update: 7/1] Convivial Party in Hiroshima Night- Guidelines for Participation / Presentation
[update: 10/29]
AWARDS
SUBMISSION/REGISTRATION
- Camera-ready Guidelines
[update:8/16] - Paper Submission and Format
[update: 6/28] - Registration
[update: 9/9]
CONTRIBUTIONS
IEEE SMC Hiroshima Chapter Invited Special Talk
Keynote Talk
Nice data mining!
Speaker
Prof. Ayahiko Niimi
Future University Hakodate, Japan
Abstract
It’s been about 10 years since the Harvard Business Review defined “Data Scientist: The Sexiest Job of the 21st Century” in 2021. Data mining and Artificial Intelligence (AI) have become widespread. They have come to be applied not only in research but also in the real world. We sometimes get consultations such as, “Please teach me about AI,” “I want to use deep learning in my business,” or “I want data mining to do a good job of analysis. What should researchers do? In response to these consultations, I will discuss three issues: 1) problems where the data are available but cannot be used immediately (pre-processing issues), 2) problems where the results are difficult to explain in an easy-to-understand manner (explainable AI), and 3) problems where the purpose of data analysis has not been decided. At first, we will talk the topic of “when we receive a consultation, there is a lot of data, but it is not ready for use.” This is a case where the “data ready” that the researcher thinks is different from the “data ready” that a general person thinks. The second topic deals with the problem that “the results presented by researchers are difficult for a general person to understand”. The researcher’s explanations of the algorithm and its results are too difficult. A general person cannot judge the data analysis result from the viewpoint of “is it useful for business?” The last topic is the most difficult. A general person vaguely thinks that “AI can do something”, but “something” does not allow researchers to set issues. We will discuss the relationship between research and practical use, what can be done from an academic standpoint.
2021年07月01日