Could the new and wildly popular chatbot ChatGPT convincingly produce fake abstracts that fool scientists into thinking those studies are the real thing? That was the question worrying Northwestern Medicine physician-scientist Dr. Catherine Gao when she designed a study--collaborating with University of Chicago scientists--to test that theory. Yes, scientists can be fooled, their new study reports. Blinded human reviewers--when given a mix real and falsely generated abstracts--could only spot ChatGPT generated abstracts 68% of the time. The reviewers also incorrectly identified 14% of real abstracts as being AI generated.

ChatGPT (Generative Pre-trained Transformer), the conversational artificial intelligence development, can write convincing fake scientific abstracts capable of fooling reviewers. This is according to a new study. In the trials, human reviewers could only detect fake abstracts, generated by the OpenAI developed software, 68 percent of the time. For the research, blinded human reviewers were given a mix of real and falsely generated abstracts and asked to sort which was which. Each reviewer was given 25 abstracts that were a mixture of the generated and original abstracts and asked to give a binary score of what they thought the abstract was.

In brief AI progresses rapidly. Just months after the release of the most advanced text-to-image models, developers are showing off text-to-video systems. Meta announced a multimodal algorithm named Make-A-Video that allows its users to type a text description of a scene as input and get a short computer-generated animated clip as output, typically depicting what was described. Other types of data, such as an image or a video, can be used as an input prompt, too. The text-to-video system was trained on public datasets, according to a non-peer reviewed paper [PDF] describing the software.

The Papermill Alarm looks for similarities to text found in bogus papers.Credit: Raimund Koch/Getty A software tool that analyses the titles and abstracts of scientific papers and detects text similar to that found in bogus articles is gaining interest from publishers. The tool, called the Papermill Alarm, was developed by Adam Day, who is director of scholarly data-services company Clear Skies in London, UK. Day says he ran all the titles listed in citation database PubMed through the system, and found that 1% of currently listed papers contain text very similar to that of articles produced by paper mills -- companies or individuals that fabricate scientific manuscripts to order. The Papermill Alarm does not say definitively whether an article is fabricated, but flags those that are worthy of further investigation. Day says his analysis is not intended to estimate the scale of paper-milling among PubMed entries, because it can recognize only papers that are similar to those from known paper mills.

The practice of science involves trying to find things out about the world by using rigid logic and testing every assumption. Researchers then write up any important findings in papers and submit them for possible publication. After a peer-review process, in which other scientists check that the research is sound, journals publish papers for public consumption. You might therefore reasonably believe that published papers are quite reliable and meet high-quality standards. You might expect small mistakes that got overlooked during peer review, but no major blunders. You'd be wrong in expecting this, though.

Kespry announced the availability of the pulp and paper industry's first drone-based aerial intelligence solution. The new industry-specific solution improves the profitability of pulp and paper operations by delivering more accurate and timely supply chain material inventory data, while improving site operations and safety. "Measuring chip piles at a pulp mill has always been a challenge. In the past, a team of surveyors would climb onto the chip pile and arrive at a manual measurement," said Mitch Dunlop, Accounting Manager, Celgar, a leading North American pulp and paper organization. "This method is slow, poses safety concerns and is not very accurate.

Mikko Marsio, Vice President of Digital Business and IoT at Empower group, says that what has unfolded over the past two decades and led companies to where they are today can be understood as both an evolution from a technological perspective, as well as a revolution from an industry and business perspective. From the speculative nature of the IT bubble, to the profoundness of the Internet of Things, Marsio explains how consolidating technology with business is now more imperative than ever before. "I remember a prediction that was made before I attended an MIT Executive Education course on the Internet in 2000. It envisioned the Internet becoming like electricity, meaning something that we don't even acknowledge when using," Marsio reminisces. "If you look at what was laid out in 2000 in conjunction with the IT bubble – for example that the best years for the pulp and paper industry were then and there – no one could actually have predicted how many paper mills would be shut down over the following 15 years. In order for these mills to stay relevant, they must adapt what they are producing. Companies in general need to understand how both digitalization and end-users are causing their businesses to change. Over the past few years, increasingly many have come to recognize this," he continues.