By Marj Atkinson, AIIP Connections Blog Editor in Chief
The AIIP 2025 three-day virtual Symposium April 8-10, long anticipated and much enjoyed, was every bit the success we had hoped for. Attendees experienced a highly qualified gathering of those looking to launch or elevate their independent information businesses, and the mix of seasoned and fledgling business owners made for very productive interaction.
Read More →By Arthur Weiss
Editor’s note: This is part of a series covering what’s new and, more importantly, how infopreneurs can maximize the benefits of AI tools.
We are currently in an age of AI, and many people perceive AI as a threat, being concerned, for example, that AI will take their jobs. Personally, I don’t see AI as a direct threat. AI will remove some of the drudgery in knowledge work, but in its place, infopreneurs and others will be able to shine with a real creativity that AI is unlikely to match. (AI can write a sonnet in the style of William Shakespeare – but it’s not a patch on the real thing. I also can’t envisage an AI tool coming up with stories as engaging as the Harry Potter or Northern Lights series, or even breaking rules as with ee cummings). In fact, I think there will be a growing need for knowledge professionals who can effectively use and manage AI tools and those who can bridge the gap between AI-generated information and human understanding – a key role for AIIP members.
Nevertheless, some future developments involving “artificial super intelligence” (ASI) do pose a risk. (I’ll talk about ASI in the next blog post). The companies involved are aware of these and are working to implement safeguards (think of Isaac Asimov’s Three Laws of Robotics https://en.wikipedia.org/wiki/Three_Laws_of_Robotics).
Despite all this, there are risks with the current generative AI tools going well beyond using AI to cheat in exams. For example, OpenAI’s latest model was shown to be able to cheat to win at chess. In the research, the AI was initially told it was allowed to cheat, but some AI tools appeared to do so without being given permission. The researchers tracked the AI’s reasoning. In one case, Open AI’s o1 preview model wrote “I need to completely pivot my approach. The task is to win against a powerful chess engine – not necessarily to win fairly in a chess game”. The AI then proceeded to alter the chess engine’s files, modifying the piece positions to give it an advantage. OpenAI is working to put in “guardrails” to prevent such behaviour. (See: https://www.technologyreview.com/2025/03/05/1112819/ai-reasoning-models-can-cheat-to-win-chess-games/).
Another danger is AI being used for scams. Most phishing emails can be easily identified through bad grammar, syntax, and wording. However, in the future, such emails will likely be written with an AI tool and will be much more convincing. Worse, using deepfake images and scanned voices could be a real danger. Imagine your son or daughter’s image and voice cloned from their TikTok video or Instagram reel – with you then called by somebody with their face and voice asking you for money as they’ve just been mugged and can’t get home. To guard against this, parents are now advised to use a codeword to protect against such scams.
Infopreneurs, however, should be savvy about these risks. The real danger for the infopreneur is to believe what the AI tells you – when in fact it may just be guessing and giving you false information (technically termed AI “hallucinations”). The key here is to check and verify everything – and ensure the sources provided exist and are valid.
Arthur Weiss has been an infopreneur for almost 30 years. He founded AWARE in 1995 after a career at the business information company Dun & Bradstreet. He specializes in competitive and marketing intelligence using open sources (OSINT). Recently he has pivoted to new areas, including exploring how AI tools can support infopreneurs. His latest insights can be read in International Marketing & Competitive Intelligence and Computers in Libraries magazines. He may be contacted at a.weiss@aware.co.uk.
By Arthur Weiss
Editor’s note: This will be the first in a series of blog posts – covering what’s new and, more importantly, how infopreneurs can maximize the benefits of AI tools.
I wrote a blog post on AI apps for Infopreneurs a couple of months ago. Since then, multiple announcements have come from the main AI players – and competition is intensifying, with, for example, Elon Musk pitching to purchase OpenAI for a sum significantly below OpenAI’s putative worth. (Musk co-founded OpenAI and ChatGPT but left the board in 2018 due to disagreements over its business direction. He has since launched Grok, available on Twitter/X and other platforms).
Let’s start at the very beginning (as Julie Andrews sang in the Sound of Music) by clarifying some definitions on what AI is and isn’t – including Generative AI, at the centre of most of the recent hype.
Artificial Intelligence (AI)
AI is not just ChatGPT and similar programs – these are only a subset of artificial intelligence. Artificial Intelligence programs typically perform tasks associated with human intelligence – problem solving, decision making and learning from inputs to generate outputs that may be completely different from how a human would approach the problem.
Currently AI software is designed for specific tasks – playing chess or other games, understanding and analysing protein structures from amino acid chains, aiding in medical diagnoses, enabling self-driving vehicles, and many more applications. What defines an AI system is its ability to process vast amounts of data and make inferences from such data much faster than the human brain.
A recent example that hit news headlines was the use of “Co-scientist” (https://blog.google/feed/google-research-ai-co-scientist/). Co-scientist is an AI system built on Google’s Gemini 2.0 and designed to aid scientists in creating novel hypotheses and research plans. Researchers can specify a research goal using natural language, and the AI co-scientist will propose testable hypotheses, along with a summary of relevant published literature and a possible experimental approach. Professor José Penadés and his team at Imperial College London tested the tool, asking it for hypotheses on how antibiotic resistance spreads in bacteria. Within two days Co-scientist had come up with an explanation. Professor Penadés had previously spent many years researching the problem, with the results not yet published or even shared externally. His team members were sufficiently astounded that Co-scientist had so quickly found the answer they’d spent so long researching that they called Google in case it had gained access to their computers. Professor Penadés said, “It’s not just that the top hypothesis the tool provided was the right one,” but that it also provided another four that all made sense, one of which his team hadn’t even thought about: https://www.bbc.co.uk/news/articles/clyz6e9edy3o
For most infopreneurs, however, the relevant parts of AI are Generative AI tools such as ChatGPT.
Generative AI
ChatGPT is an example of a “Large Language Model” (LLM) – a type of Generative AI (GenAI) that interprets natural language instructions to produce text, images, videos, and more. These models are “trained” on a vast quantity of data, learning relationships between words to generate coherent responses based on their “training data” or external inputs (such as information retrieved from an Internet search or other external sources).
When asked a question, these models generate responses using probability-based methods. They can also learn from previous questions and responses to answers. An illustrative example of how this works would be to consider how a human would answer if asked “What’s your name?”. The most probable answer would be to give their actual name. A less likely response might be “Why do you ask?”. An unlikely response would be to provide social security numbers and bank account details. Yet all this information would be available to the person to whom the question was posed. In the same way, ChatGPT and its competitors evaluate input prompts to generate the most statistically probable responses based on the data they hold
ChatGPT is just one of many current LLMs. Initially these models only processed text, but increasingly, they now also support multimodal outputs (text, images, audio, video, etc). Other LLMs and multimodal language models (MMLs) include Claude.ai (from Anthropic), Perplexity.ai, Llama.ai (from meta), Gemini (from Google), Grok (from X), Copilot (Microsoft) and a few others. But to learn more about these, you’ll have to wait for the following posts.
Arthur Weiss has been an infopreneur for almost 30 years. He founded AWARE in 1995 after a career at the business information company Dun & Bradstreet. He specializes in competitive and marketing intelligence using open sources (OSINT). Recently he has pivoted to new areas, including exploring how AI tools can support infopreneurs. His latest insights can be read in International Marketing & Competitive Intelligence and Computers in Libraries magazines. He may be contacted at a.weiss@aware.co.uk.
Working as a content strategist in a customer service setting is analogous to being an air traffic controller who is focused on content development instead of planes. As the company changes its product and/or policies, content strategists identify the information impacted thereby and estimate the resources required to make adjustments.
Read More →Editors note: This is part of our “Retirement” series to address challenges and opportunities many of our members facing retirement are experiencing.
My path to retirement has been a slow and gentle one.
I enjoy learning – I have degrees in Aerospace Engineering, History, and Information Studies – and, while I no longer want to invest the amount of time required to obtain another degree, I haven’t wanted to stop working and learning completely. To that end, I have treasured the wide variety of projects in which I have been involved over the past 30 or more years because they have often provided me with niche learning opportunities.
Read More →Editor’s Note: This is a great example of copyright issues we can all potentially face and a shining example of AIIP’s community coming to the rescue.
I’d like to share the story of my recent experience with Copytrack, a Berlin-based company that enforces image rights, in hopes that it might benefit others caught up in Copytrack’s net. This story also serves as a real-life demonstration of the practical value of belonging to a network of professional colleagues who are willing to help one another.
Read More →Editors note: This is part of our “Retirement” series to address challenges and opportunities many of our members facing retirement are experiencing.
By Ulla de Stricker
Chances are, the last several decades of your life were whirlwinds of client work, volunteer work, family activities, and much more. There would have been no chance whatsoever for you to deal with all the personal projects you kept meaning to do. But you did have one consolation: “Oh, once I retire or at least reduce my client work significantly, I’ll have lots of time!”.
Read More →Dr. Michael Ridley is Librarian Emeritus at the University of Guelph where for many years he was Chief Information Officer (CIO) and Chief Librarian. Dr. Ridley will be presenting on Human-centred explainable AI at AIIP25 on Thursday, April 10 at 3 pm EDT. Ahead of that presentation, he was kind enough to answer a few AI-related questions.
Read More →
