Do Machines Have Rights? Ethics in the Age of Artificial Intelligence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dr. David Gunkel Currently holds the position of Presidential Teaching Professor in the Department of Communication at Northern Illinois University, where he develops and teaches courses in web design and programming, information and communication technology (ICT), and cyberculture. His research and publications examine the philosophical assumptions and ethical consequences of ICT. He has published four books. He lectures and delivers award-winning papers throughout North America and Europe and he serves as the managing editor of the International Journal of Žižek Studies. His teaching has been recognized with numerous awards, including NIU's Excellence in Undergraduate Teaching Award (EUTA) in 2006 and the Presidential Teaching Professorship in 2009. David J. Gunkel was the keynote speaker for “Identity, Agency, and the Digital Nexus”, April 2013, an international symposium hosted by Athabasca University. His talk challenged the audience to reframe and rethink the “human-machine” binary in 21st century understandings of ethics and agency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it