I read Alex G Smith's recent LinkedIn post, which first made me laugh, and then gave me major flashbacks to the March 2018 CLSIG event where he was the speaker. Fact check: I can confirm he coined the phrase "IA before AI" in that session.
Despite it being 6 years ago, his session on "Information architecture and artificial intelligence" remains relevant. At the time, I wrote that it was a timely wake-up call for how machine learning should be perceived; instead of horror movie AI robots, our real nightmare is messy data. We are potentially reliant on poor quality and imbalanced, or even private data for training AI - this is still the stuff of nightmares in 2024.
At the time, we thought that we had been offering and using a certain level of AI in our roles but in reality, this was essentially nothing more than data management and algorithms. Analytics and automatic documentation is not AI. Over the past few years, we have expanded our technical vocabulary - ChatGPT, GenAI, LLMs etc. We have learned that GenAI is,
...an advanced predictive text autocomplete machine. It determines the most reasonable continuation of a sentence based on patterns it has learned from vast amounts of data. You can find out more about ChatGPT here and how it’s evolving here. It's crucial to note that ChatGPT, like the other AI models, doesn't understand the language it generates. It is both shockingly smart and shockingly stupid!
The session in 2018 mentioned "filter bubbles". This concept was first coined by Eli Pariser in 2011, and depending on the intentions of the publisher or advertiser, they can be used for good or bad. Our online consumption habits remain a dream for contextual search engines, targeted advertising or political manipulation. But it can also enable all types of organisations to recommend related information, products, music, books, videos etc.
I suspect that filter bubbles are now the least of our worries. Very soon, the information being served up in our Google searches might be a product of GenAI. Google said at its 2024 I/O developer event that it’s rolling out its AI-native search to all users for the first time. People have been experimenting with Google’s chatbot-based search, which is called the “Search Generative Experience” (SGE). This development has massive implications for consumers, businesses, and content creators!
While OpenAI’s ChatGPT is a novel product, consumers have spent years with Google and expect search results to be fast and accurate. The rush into generative AI might also run up against legal problems. The underlying tech behind OpenAI, Google, Meta and Microsoft’s AI was trained on millions of news articles, blog posts, e-books, recipes, social media comments and Wikipedia pages that were scraped from the internet without paying or asking permission of their original authors. WSJ, 13th May, 2024
However, the blending of AI with search technologies brings new challenges and ethical considerations. The evolution of AI-native searches will likely amplify concerns about filter bubbles, data privacy and the accuracy of information. As generative AI becomes more integrated into everyday tools, we must remain vigilant about the sources and integrity of the data it relies upon, ensuring that it serves to inform and not mislead.
At the time of Alex's session, Cambridge Analytica was in the news regarding its descent into administration following the fallout from the Facebook data harvesting scandal. Clearly, privacy matters have not improved! Since then, the EU's implementation of the General Data Protection Regulation (GDPR) in May 2018, numerous fines have been issued for violations or non-compliance.
Of these, the fine of €1.2 billion received by Meta Platforms in May 2023 has been by far the greatest. The company was issued such a large penalty for personal data transfers to the US without sufficiently complying with the EU regulation. These recent statistics demonstrate that the legislation has power but is it enough to change corporate attitudes to the protection of consumer/personal data?
Highest fines issued for General Data Protection Regulation (GDPR) violations as of January 2024 (Statista)
But still, people continue to mingle on social media platforms and our behaviour hasn’t changed that much. In many ways, we are still willfully ignorant about this data mess. How many people actually read app/site terms and conditions? How many people are willing to give information to organisations simply because they wanted free WiFi? Or allow sites access to personal profiles just to access a quiz?
‘Humans are excellent at creating mess. We are currently polluting ourselves with unstructured data, and unrealistically expecting AI - or machine learning - to clean it all up"
But what of the law? Law and legal language can be relatively logical. Legal and business knowledge collection depends on legal updates, procedures, flowcharts, checklists, and taxonomies. It has taken a lot of information management effort to reach this stage. To take Alex’s phrase, 'IA (information architecture) before AI.' But what next? Will GenAI mean the end of lawyers?
As Artificial Lawyer notes, the outlook for the legal industry is positive:
At present, genAI is steadily seeing uptake mostly across the larger law firms and major inhouse legal teams. And that’s a great start – it’s also highly predictable that it would begin there...
...Likewise, it could in many ways be the opening up of a new era for legal technology as it finally helps set us on the path to fully achieve the productive transformation it is capable of, but has not been allowed to do in the past. And it’s worth saying the loss of lawyer roles is not the real threat here. The biggest risk is that the legal world fails to seize this opportunity. Splitting the legal information atom with generative AI won’t blow up the legal world, it will give it a new lease of life. The future is in our hands – we just have to decide to shape it.
The major legal and business publishers have all the structured and reliable information they need to offer the legal industry a new lease on life. AI solutions from vLex, Lexis, Thomson Reuters, and others have revolutionised access to their various resources. For example, vLex's AI, Vincent, provides comprehensive research capabilities by analysing vast databases of legal information. It's an exciting time!
The swift progress of AI technology in the legal sector might have caught many by surprise, but it presents an unprecedented opportunity for library and information people to make an impact. Law librarians and information professionals must refine their skills, maintain their relevance, and facilitate effective change management.
Given that law is data-heavy and we (as information people, legal experts, business services professionals and most importantly, clients!) are not robots, there will always be a need for making connections and applying human judgment and experience. Rather than focusing solely on the right answers, we should embrace our human ability to explore and incorporate multiple viewpoints. Only then will we make AI work in a truly human way, with genuine respect for data protection and integrity. Do you agree?
#IAbeforeAI - Thanks Alex!