Chris Norval
Biographic Data
| ID | 6763994 |
|---|---|
| NAME | Chris Norval |
| GIVEN NAMES | Chris |
| FAMILY NAME | Norval |
| SIGNATURE | NORVAL C |
| AFFILIATIONS | University of Cambridge |
| ORCID | 0000-0002-4331-7863 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
Data protection and tech startups
Though discussions of data protection have focused on the larger, more established organisations, startups also warrant attention. This is particularly so for tech startups, who are often innovating at the ‘cutting‐edge’—pushing the boundaries of technologies that typically lack established data protection best‐practices. Initial decisions taken by startups could well have long‐term impacts, and their actions may inform (for better or for worse) …
Automating Dynamic Consent Decisions for the Processing of Social Media Data in Health Research
Social media have become a rich source of data, particularly in health research. Yet, the use of such data raises significant ethical questions about the need for the informed consent of those being studied. Consent mechanisms, if even obtained, are typically broad and inflexible, or place a significant burden on the participant. Machine learning algorithms show much promise for facilitating a "middle-ground" approach: using trained models to pre…
Automating Dynamic Consent Decisions for the Processing of Social Media Data in Health Research
Social media have become a rich source of data, particularly in health research. Yet, the use of such data raises significant ethical questions about the need for the informed consent of those being studied. Consent mechanisms, if even obtained, are typically broad and inflexible, or place a significant burden on the participant. Machine learning algorithms show much promise for facilitating a "middle-ground" approach: using trained models to pre…
Automating Dynamic Consent Decisions for the Processing of Social Media Data in Health Research
Social media have become a rich source of data, particularly in health research. Yet, the use of such data raises significant ethical questions about the need for the informed consent of those being studied. Consent mechanisms, if even obtained, are typically broad and inflexible, or place a significant burden on the participant. Machine learning algorithms show much promise for facilitating a "middle-ground" approach: using trained models to pre…
Data protection and tech startups
Though discussions of data protection have focused on the larger, more established organisations, startups also warrant attention. This is particularly so for tech startups, who are often innovating at the ‘cutting‐edge’—pushing the boundaries of technologies that typically lack established data protection best‐practices. Initial decisions taken by startups could well have long‐term impacts, and their actions may inform (for better or for worse) …
Computer Science (2 works) · Ethics and Social Impacts of AI (2 works) · Law (2 works) · Political science (2 works) · Alternative medicine (1 work) · Artificial Intelligence (1 work) · Business (1 work) · Computer security (1 work) · Data Protection Act 1998 (1 work) · Data science (1 work)