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If you are a student or working in the academic world, the following is probably a familiar scenario to you. You sit at a desk and ahead of you lies a big task: you must research a certain topic in-depth and return all the relevant, valuable information you can find. This means reading tons of research papers, generating an understanding of them, and synthesizing all the important information you need in a comprehensive text. It goes without saying that this task, also known as the literature review, is very arduous and therefore one of the most dreaded parts of the scientific process. Over the last few years however, technologies have been developed that might just save the day. One technology in particular has been gaining popularity over the last few months.

Consensus is a website powered by a generative AI. It is described by some as the imaginary baby of ChatGPT and Google Scholar. In essence, this website is a powerful search engine that allows its users to ask it questions to which it will respond by giving an overview of all the relevant scientific articles it can find. Let’s say you just saw a video of a gorilla communicating with a human using sign language. This piqued your curiosity so much that you got curious about the communicative abilities of gorillas. If you now type in the question: “Can gorillas effectively communicate with humans?” into Consensus, it will tell you the following: The ability of gorillas to communicate effectively with humans has been a subject of interest in understanding the cognitive and social capabilities of these primates. Research has explored various aspects of gorilla communication, including their use of gestures, vocalizations, and sensitivity to human attentional states. This short introduction would then be followed up by a summary of the key findings and their respective references, followed up with a separate list of all the relevant studies. All the studies would be linked directly as to make them as accessible as possible, allowing for a very fast exploration of a single topic.

Given the number of studies that are referenced in a single search and the amount of summarizing that is done, it is safe to say that Consensus could save people hours upon hours of time. No longer do you need to try endless amounts of different search terms, scan through papers with hundreds of pages and make endless lists of research notes. This is all great news as the use of AI for research purposes has the potential to make research more efficient and perhaps even more enjoyable. There is however also reason to be somewhat skeptical of a technology like this.

First and foremost, making artificial intelligence our one and only source of information should never be standard practice, especially in the academic world. Even if we are just using AI as a tool to find new papers, there is always the chance that the AI makes a big oversight and leaves out key information, or worse, AI could misrepresent the information and lead researchers to the wrong conclusions. Sites like Consensus are therefore best used in tandem with researchers own research, as just another tool in the toolbox. Because no matter where the information is coming from, it’s the researcher’s responsibility to make sure all the information in their work is factually correct and truthful. At the end of the day, being an arbiter of truth is a job best suited to humans, not machines.

Thumbnail credit: https://consensus.app/home/wp-content/uploads/2022/07/Horizontal-product-background-2×1-1.png
Image Credit: https://www.wikihow.com/images/8/8a/Take-Notes-for-Your-Research-Paper-Step-5.jpg

References:
Bello, C. (2024, January 20). The best AI tools to power your academic research. Euronews. https://www.euronews.com/next/2024/01/20/best-ai-tools-academic-research-chatgpt-consensus-chatpdf-elicit-research-rabbit-scite

Consensus AI. (2024, May 29). Introducing: Consensus GPT, your AI Research assistant – Consensus: AI search engine for research. Consensus: AI Search Engine for Research. https://consensus.app/home/blog/introducing-researchgpt-by-consensus/

Foster, G. (2024, September 23). How to Use Consensus: A guide to AI-Powered research. AIPure. https://aipure.ai/articles/how-to-use-consensus-a-guide-to-ai-powered-research

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In the late 90’s, getting music into your home was a process of going to the store, buying a CD, going back home, and putting that CD in a CD player. In 1999, this would all change with the rise of the computer application Napster. Build by two then students, Shawn Fanning and Sean Parker, it would change the music industry forever.

The Napster story is really a tale about big industries failing to catch up with digitalization. By the late 90’s all the technologies to easily and readily share files were there. Homes had personal computers on which different file types were stored, and these file types could easily, if slowly, be sent to other users across the internet. Napster utilized peer to peer networks, where users could access and download the songs off the hard drives of other users. Napster wasn’t even the only application to offer services like this. Networks like IRC, Hotline and Usenet were already out there, what separated Napster from them was its user friendliness and focus on mp3 audio files (Gowan, 2002). In a way, something similar to Shawn Fanning and Sean Parker creating and launching Napster was always going to happen, they were just the first to do so.

Of course, the music industry and RIAA (the Recording Industry Association of American) specifically, wouldn’t let a program like Napster slide that easily. Almost from its inception onwards, Napster would face lawsuits which would eventually lead to their shutdown in July of 2001, but not before reaching a peak of 80 million registered users (Creager, 2019). By this point however, other programs like LimeWire, Kazoo and BitTorrent had popped up, each of which performed similar services as Napster. No matter how many court cases the music industry started, it seemed like the floodgates were now opened, and it was too late to go back to the CD based distributing of the past.

In the same year that Napster shut down, Steve Jobs launched the first digital store for music, called iTunes. Here, users could acquire their digital music legally. Music companies faced a tough decision: either have Apple distribute their music for them on the internet against very low margins or refuse to go digital and watch on as people pirate their music anyways. A decade after that, Spotify launched, using a different, subscription-based model to give users access to an almost endless supply of music.

It’s fair to say that the music industry never really recovered from the shockwave Napster put into motion. Today, artists make a lot less money than they used to, mainly getting by on the popularity and tours the digital distribution permits them (Sisaro, 2021). This also is maybe the silver lining for artists, because while the digitalization of the music industry has brough with it dramatic revenue cuts, it also allows users to find and enjoy artists that they would otherwise have never heard of.

Thumbnail credit: https://www.informacyde.com/blog/music/mon-avis-sur-napster/

Image credit: https://musicatyourfingertipss.weebly.com/napster–its-evolution.html

References

Creager, R. (2019, July 26). Short song: The Rise and Fall of Napster – Inventors Digest. Inventors Digest. https://www.inventorsdigest.com/articles/short-song-the-rise-and-fall-of-napster/

Gowan, M. (2002, May 18). Requiem for Napster. Pcworld. Retrieved September 17, 2024, from https://web.archive.org/web/20140426235542/http://www.pcworld.idg.com.au/article/22380/requiem_napster/

Sisaro, B. (2021, May 7). Musicians Say Streaming Doesn’t Pay. Can the Industry Change? Nytimes. Retrieved September 17, 2024, from https://www.nytimes.com/2021/05/07/arts/music/streaming-music-payments.html