The Robot as Cub Reporter: Law's Emerging Role in Cognitive Journalism
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
\n\t\t\t\t\tToday's journalist is immersed in news production that no longer treats robot-written news as a mere reference tool. Major news corporations are reshaping the journalism business to reflect the increasingly dominant role of algorithms and its consequent decrease in human curation. With data so integral to today's news storytelling and the arrival of machines that are learning to 'sense, think and act' like their creators, we are called to deliberate on the legitimacy of law to address human risks and responsibilities when humans are harmed physically, socially, financially or professionally. This paper argues that we are entering the age of cognitive journalism that affects the legal personhood question and examines policy initiatives on both sides of the Atlantic for legal norms to inform a law for machines that learn from mistakes and teach other machines. Legal issues raised by driverless cars, human cloning, drones and nanotechnology are examined for what they can offer to an emerging law of the robot. The paper concludes with a call for research that will bring a more nuanced understanding of the legitimate place of law in cognitive journalism.\n\t\t\t\t
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 | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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