Tina Law
Datos Biográficos
| ID | 4122773 |
|---|---|
| NOMBRE | Tina Law |
| NOMBRES | Tina |
| APELLIDO | Law |
| FIRMA | LAW T |
| AFILIACIONES | University of California, Davis |
| ORCID | 0000-0001-7631-6763 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 7 |
| TOTAL DE CITAS | 12 |
| TOTAL COMO AUTOR | 7 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2018 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 3 |
Why Democratic Deliberation and Governance of AI Matters
Tina Law on current ai regulation and why it fails
Unpacking the Politics of the US Deportation System
There is a growing multidisciplinary effort to understand the political causes and consequences of the US deportation system amid rapidly changing policies and significant data limitations. I contribute to this timely work by considering how interactions between an increasingly empowered executive branch and a politically polarized Congress shape deportation policymaking. I apply a policy feedback approach, a theoretical lens that analyzes polici…
Generative Multimodal Models for Social Science
Although there is growing social science research examining how generative AI models can be effectively and systematically applied to text-based tasks, whether and how these models can be used to analyze images remain open questions. In this article, we introduce a framework for analyzing images with generative multimodal models, which consists of three core tasks: curation, discovery, and measurement and inference. We demonstrate this framework …
Updating 'The Future of Coding
Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using natural language, potentially mimicking the in-depth, inductive, and/or iterative process of qualita…
Training Computational Social Science PhD Students for Academic and Non-Academic Careers
Social scientists with data science skills increasingly are assuming positions as computational social scientists in academic and non-academic organizations. However, because computational social science (CSS) is still relatively new to the social sciences, it can feel like a hidden curriculum for many PhD students. To support social science PhD students, this article is an accessible guide to CSS training based on previous literature and our col…
Artificial Intelligence Policymaking
Sociological research on artificial intelligence (AI) is flourishing: sociologists of inequality are examining new and concerning effects of AI on American society, and computational sociologists are developing novel ways to use AI in research. The authors advocate for a third form of sociological engagement with AI: research on how AI can be publicly governed to advance equity in American society. The authors orient sociologists to the rapidly e…
Urban Data Science
Data on urban life are more accessible today than ever before. New sources of “big data” such as 311 requests, recorded police activity, digitized student records, and social media capture urban life on an unprecedented temporal and geographical scale. Combined with new and improved computational social science methods for harnessing data, they promise to change urban research in important ways. In this essay, we outline urban data science—an eme…
Updating 'The Future of Coding
Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using natural language, potentially mimicking the in-depth, inductive, and/or iterative process of qualita…
Artificial Intelligence Policymaking
Sociological research on artificial intelligence (AI) is flourishing: sociologists of inequality are examining new and concerning effects of AI on American society, and computational sociologists are developing novel ways to use AI in research. The authors advocate for a third form of sociological engagement with AI: research on how AI can be publicly governed to advance equity in American society. The authors orient sociologists to the rapidly e…
Training Computational Social Science PhD Students for Academic and Non-Academic Careers
Social scientists with data science skills increasingly are assuming positions as computational social scientists in academic and non-academic organizations. However, because computational social science (CSS) is still relatively new to the social sciences, it can feel like a hidden curriculum for many PhD students. To support social science PhD students, this article is an accessible guide to CSS training based on previous literature and our col…
Generative Multimodal Models for Social Science
Although there is growing social science research examining how generative AI models can be effectively and systematically applied to text-based tasks, whether and how these models can be used to analyze images remain open questions. In this article, we introduce a framework for analyzing images with generative multimodal models, which consists of three core tasks: curation, discovery, and measurement and inference. We demonstrate this framework …
Urban Data Science
Data on urban life are more accessible today than ever before. New sources of “big data” such as 311 requests, recorded police activity, digitized student records, and social media capture urban life on an unprecedented temporal and geographical scale. Combined with new and improved computational social science methods for harnessing data, they promise to change urban research in important ways. In this essay, we outline urban data science—an eme…
Training Computational Social Science PhD Students for Academic and Non-Academic Careers
Social scientists with data science skills increasingly are assuming positions as computational social scientists in academic and non-academic organizations. However, because computational social science (CSS) is still relatively new to the social sciences, it can feel like a hidden curriculum for many PhD students. To support social science PhD students, this article is an accessible guide to CSS training based on previous literature and our col…
Artificial Intelligence Policymaking
Sociological research on artificial intelligence (AI) is flourishing: sociologists of inequality are examining new and concerning effects of AI on American society, and computational sociologists are developing novel ways to use AI in research. The authors advocate for a third form of sociological engagement with AI: research on how AI can be publicly governed to advance equity in American society. The authors orient sociologists to the rapidly e…
Unpacking the Politics of the US Deportation System
There is a growing multidisciplinary effort to understand the political causes and consequences of the US deportation system amid rapidly changing policies and significant data limitations. I contribute to this timely work by considering how interactions between an increasingly empowered executive branch and a politically polarized Congress shape deportation policymaking. I apply a policy feedback approach, a theoretical lens that analyzes polici…
Generative Multimodal Models for Social Science
Although there is growing social science research examining how generative AI models can be effectively and systematically applied to text-based tasks, whether and how these models can be used to analyze images remain open questions. In this article, we introduce a framework for analyzing images with generative multimodal models, which consists of three core tasks: curation, discovery, and measurement and inference. We demonstrate this framework …
Updating 'The Future of Coding
Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using natural language, potentially mimicking the in-depth, inductive, and/or iterative process of qualita…
Why Democratic Deliberation and Governance of AI Matters
Tina Law on current ai regulation and why it fails
Computer Science (4 obras) · Computational and Text Analysis Methods (3 obras) · Social science (3 obras) · Sociology (3 obras) · Artificial Intelligence (2 obras) · Artificial Intelligence (2 obras) · Corporate governance (2 obras) · Democracy (2 obras) · Engineering (2 obras) · Ethics and Social Impacts of AI (2 obras)