Pub Date : 2019-06-22DOI: 10.1162/99608F92.38F16B68
L. Haas, A. Hero, R. Lue
In 2016, the National Academies of Sciences, Engineering, and Medicine of the United States established the Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective. The committee issued a 120-page report in 2018, setting forth a vision for the undergraduate education in data science. This interview of the co-chairs of the committee, Laura Haas, the Dean of the College of Information and Computer Sciences at University of Massachusetts at Amherst, and Alfred Hero, the co-director of the Michigan Institute for Data Science, is conducted by Rob Lue, the co-editor of data science education for Harvard Data Science Review. It provides a succinct summary of the key findings and recommendations of the Report, highlighting the call to equip students with “data acumen.” It also probes beyond the Report, including the possible roles of data science for reimagining liberal arts education in the digital age.KeywordsData Acumen, Data Ethics, Data Science Curriculum, Data Science Programs, Digital-age Education, Liberal Arts Education
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Pub Date : 2019-06-22DOI: 10.1162/99608F92.17405BB6
S. Leonelli
I provide a philosophical perspective on the characteristics of data-centric research and the conceptualization of data that underpins it. The transformative features of contemporary data science derive not only from the availability of Big Data and powerful computing, but also from a fundamental shift in the conceptualization of data as research materials and sources of evidence. A relational view of data is proposed, within which the meaning assigned to data depends on the motivations and instruments used to analyze them and to defend specific interpretations. The presentation of data, the way they are identified, selected and included (or excluded) in databases and the information provided to users to re-contextualize them are fundamental to producing knowledge - and significantly influence its content. Concerns around interpreting data and assessing their quality can be tackled by cultivating governance strategies around how data are collected, managed and processed.Keywordsdata philosophy; data history; data-centric research; inference; data management; data curation; modelling.
{"title":"Data Governance is Key to Interpretation: Reconceptualizing Data in Data Science","authors":"S. Leonelli","doi":"10.1162/99608F92.17405BB6","DOIUrl":"https://doi.org/10.1162/99608F92.17405BB6","url":null,"abstract":"I provide a philosophical perspective on the characteristics of data-centric research and the conceptualization of data that underpins it. The transformative features of contemporary data science derive not only from the availability of Big Data and powerful computing, but also from a fundamental shift in the conceptualization of data as research materials and sources of evidence. A relational view of data is proposed, within which the meaning assigned to data depends on the motivations and instruments used to analyze them and to defend specific interpretations. The presentation of data, the way they are identified, selected and included (or excluded) in databases and the information provided to users to re-contextualize them are fundamental to producing knowledge - and significantly influence its content. Concerns around interpreting data and assessing their quality can be tackled by cultivating governance strategies around how data are collected, managed and processed.Keywordsdata philosophy; data history; data-centric research; inference; data management; data curation; modelling.","PeriodicalId":23712,"journal":{"name":"Volume 4 Issue 1","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87343650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-20DOI: 10.1162/99608F92.FF7CA64E
E. Candès, John C. Duchi, C. Sabatti
{"title":"Comments on Michael Jordan’s Essay “The AI Revolution Hasn’t Happened Yet\"","authors":"E. Candès, John C. Duchi, C. Sabatti","doi":"10.1162/99608F92.FF7CA64E","DOIUrl":"https://doi.org/10.1162/99608F92.FF7CA64E","url":null,"abstract":"","PeriodicalId":23712,"journal":{"name":"Volume 4 Issue 1","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76304029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-20DOI: 10.1162/99608F92.EE412EDD
Brendan McCord
{"title":"Taking Up the Revolutionary Call: Principles to Guide a Purpose-Driven AI Future","authors":"Brendan McCord","doi":"10.1162/99608F92.EE412EDD","DOIUrl":"https://doi.org/10.1162/99608F92.EE412EDD","url":null,"abstract":"","PeriodicalId":23712,"journal":{"name":"Volume 4 Issue 1","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90238036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-18DOI: 10.1162/99608F92.0C23C330
M. Fasli
{"title":"Commentary on Artificial Intelligence – the Revolution Hasn’t Happened Yet by Michael J. Jordan, University of California, Berkeley","authors":"M. Fasli","doi":"10.1162/99608F92.0C23C330","DOIUrl":"https://doi.org/10.1162/99608F92.0C23C330","url":null,"abstract":"","PeriodicalId":23712,"journal":{"name":"Volume 4 Issue 1","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89262215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-18DOI: 10.1162/99608F92.B9006D09
Michael I. Jordan
{"title":"Dr. AI or: How I Learned to Stop Worrying and Love Economics","authors":"Michael I. Jordan","doi":"10.1162/99608F92.B9006D09","DOIUrl":"https://doi.org/10.1162/99608F92.B9006D09","url":null,"abstract":"","PeriodicalId":23712,"journal":{"name":"Volume 4 Issue 1","volume":"88 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77390658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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