Category: Artificial Intelligence/Robots

We have developed and launched an easy-to-use platform for conducting large-scale qualitative interviews, based on artificial intelligence in just this way. A chat interface allows the respondent to interact with a LLM that collects their responses and generates new questions. . . .

First, we asked a team of sociology PhD students from Harvard and the London School of Economics, who specialise in qualitative methods, to assess the quality of interviews based on the interview scripts. The AI-led interviews were rated approximately comparable to an average human expert (under the same conditions). . . . A vast majority of participants reported enjoying their interaction with the conversational agent and preferred this mode of interview over open text fields.

https://tinyurl.com/mry3vrat

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |

When OpenAI got its giant investment from Microsoft, it agreed to an exclusive deal to buy computing power from Microsoft and work closely with the tech giant on new A.I.. . . .

OpenAI employees complain that Microsoft is not providing enough computing power. . . some have complained that if another company beat it to the creation of A.I. that matches the human brain, Microsoft will be to blame because it hasn’t given OpenAI the computing power it needs. . . .

The contract contains a clause that says that if OpenAI builds artificial general intelligence, or A.G.I. — roughly speaking, a machine that matches the power of the human brain — Microsoft loses access to OpenAI’s technologies.

The clause was meant to ensure that a company like Microsoft did not misuse this machine of the future, but today, OpenAI executives see it as a path to a better contract. . . Under the terms of the contract, the OpenAI board could decide when A.G.I. has arrived.

https://tinyurl.com/y5mjr66d

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |

Time spent by academics on research quality assessment might be reduced if automated approaches can help. Whilst citation-based indicators have been extensively developed and evaluated for this, they have substantial limitations and Large Language Models (LLMs) like ChatGPT provide an alternative approach. This article assesses whether ChatGPT 4o-mini can be used to estimate the quality of journal articles across academia. It samples up to 200 articles from all 34 Units of Assessment (UoAs) in the UK’s Research Excellence Framework (REF) 2021, comparing ChatGPT scores with departmental average scores. There was an almost universally positive Spearman correlation between ChatGPT scores and departmental averages, varying between 0.08 (Philosophy) and 0.78 (Psychology, Psychiatry and Neuroscience), except for Clinical Medicine (rho=-0.12). Although other explanations are possible, especially because REF score profiles are public, the results suggest that LLMs can provide reasonable research quality estimates in most areas of science, and particularly the physical and health sciences and engineering, even before citation data is available. Nevertheless, ChatGPT assessments seem to be more positive for most health and physical sciences than for other fields, a concern for multidisciplinary assessments, and the ChatGPT scores are only based on titles and abstracts, so cannot be research evaluations.

https://arxiv.org/abs/2409.16695

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |

Within three months of the rollout [of a long-term conversation memory feature], [Johann] Rehberger found that memories could be created and permanently stored through indirect prompt injection, an AI exploit that causes an LLM to follow instructions from untrusted content such as emails, blog posts, or documents. The [security] researcher demonstrated how he could trick ChatGPT into believing a targeted user was 102 years old, lived in the Matrix, and insisted Earth was flat and the LLM would incorporate that information to steer all future conversations.. . .

While OpenAI has introduced a fix that prevents memories from being abused as an exfiltration vector, the researcher said, untrusted content can still perform prompt injections that cause the memory tool to store long-term information planted by a malicious attacker.

https://tinyurl.com/bddcxjj4

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |

In our tests, the next model update performs similarly to PhD students on challenging benchmark tasks in physics, chemistry, and biology. We also found that it excels in math and coding. In a qualifying exam for the International Mathematics Olympiad (IMO), GPT-4o [the last model] correctly solved only 13% of problems, while the [new]reasoning model scored 83%. Their coding abilities were evaluated in contests and reached the 89th percentile in Codeforces competitions. . . .

As an early model, it doesn’t yet have many of the features that make ChatGPT useful, like browsing the web for information and uploading files and images. For many common cases GPT-4o will be more capable in the near term.

https://tinyurl.com/5ap6p996

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |

The datacenter industry is set to emit 2.5 billion tonnes of greenhouse gas (GHG) emissions worldwide between now and the end of the decade, three times more than if generative AI had not been developed.

https://tinyurl.com/4vatmm8a

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |

Yet, although current LLMs. . ., including GPT-3, were trained on predominantly human-generated text, this may change. If the training data of most future models are also scraped from the web, then they will inevitably train on data produced by their predecessors. In this paper, we investigate what happens when text produced by, for example, a version of GPT forms most of the training dataset of following models. . . .

Model collapse is a degenerative process affecting generations of learned generative models, in which the data they generate end up polluting the training set of the next generation. Being trained on polluted data, they then mis-perceive reality. . . .

In our work, we demonstrate that training on samples from another generative model can induce a distribution shift, which—over time—causes model collapse. This in turn causes the model to mis-perceive the underlying learning task. To sustain learning over a long period of time, we need to make sure that access to the original data source is preserved and that further data not generated by LLMs remain available over time. The need to distinguish data generated by LLMs from other data raises questions about the provenance of content that is crawled from the Internet: it is unclear how content generated by LLMs can be tracked at scale. One option is community-wide coordination to ensure that different parties involved in LLM creation and deployment share the information needed to resolve questions of provenance. Otherwise, it may become increasingly difficult to train newer versions of LLMs without access to data that were crawled from the Internet before the mass adoption of the technology or direct access to data generated by humans at scale.

https://doi.org/10.1038/s41586-024-07566-y

See also: “When A.I.’s Output Is a Threat to A.I. Itself.”

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |