The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry
While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the scientific community and society as a whole. An...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | deu |
| Published: |
Swiss Chemical Society
2023-02-01
|
| Series: | CHIMIA |
| Subjects: | |
| Online Access: | https://www.chimia.ch/chimia/article/view/6226 |
| _version_ | 1797866142884167680 |
|---|---|
| author | Daniel Probst |
| author_facet | Daniel Probst |
| author_sort | Daniel Probst |
| collection | DOAJ |
| description | While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the scientific community and society as a whole. An ever-growing need for more computational resources may exacerbate the concentration of funding, the exclusiveness of research, and thus the inequality between countries, sectors, and institutions. Here, I introduce recent concerns and considerations of the machine learning research community that could affect chemistry and present potential solutions, including more detailed assessments of model performance, increased adherence to open science and open data practices, an increase in multinational and multi-institutional collaboration, and a focus on thematic and cultural diversity. |
| first_indexed | 2024-04-09T23:19:23Z |
| format | Article |
| id | doaj.art-226e35f8b4f348ed957f73f60356e9f0 |
| institution | Directory Open Access Journal |
| issn | 0009-4293 2673-2424 |
| language | deu |
| last_indexed | 2024-04-09T23:19:23Z |
| publishDate | 2023-02-01 |
| publisher | Swiss Chemical Society |
| record_format | Article |
| series | CHIMIA |
| spelling | doaj.art-226e35f8b4f348ed957f73f60356e9f02023-03-22T01:09:50ZdeuSwiss Chemical SocietyCHIMIA0009-42932673-24242023-02-01771/210.2533/chimia.2023.56The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for ChemistryDaniel Probst0School of Engineering, EPFLWhile the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the scientific community and society as a whole. An ever-growing need for more computational resources may exacerbate the concentration of funding, the exclusiveness of research, and thus the inequality between countries, sectors, and institutions. Here, I introduce recent concerns and considerations of the machine learning research community that could affect chemistry and present potential solutions, including more detailed assessments of model performance, increased adherence to open science and open data practices, an increase in multinational and multi-institutional collaboration, and a focus on thematic and cultural diversity.https://www.chimia.ch/chimia/article/view/6226Drug discoveryMachine learningOrganic chemistry |
| spellingShingle | Daniel Probst The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry CHIMIA Drug discovery Machine learning Organic chemistry |
| title | The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry |
| title_full | The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry |
| title_fullStr | The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry |
| title_full_unstemmed | The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry |
| title_short | The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry |
| title_sort | societal and scientific importance of inclusivity diversity and equity in machine learning for chemistry |
| topic | Drug discovery Machine learning Organic chemistry |
| url | https://www.chimia.ch/chimia/article/view/6226 |
| work_keys_str_mv | AT danielprobst thesocietalandscientificimportanceofinclusivitydiversityandequityinmachinelearningforchemistry AT danielprobst societalandscientificimportanceofinclusivitydiversityandequityinmachinelearningforchemistry |