For many, the term web 2.0 is not an easy sell, as it has been used and abused for both defining a way to design things as well as types of community services that really engage people to participate. So when I cam across the McKinsey report about how companies can use web 2.0, I was wondering whether the article was going to make me cringe or not. McKinsey are not really well known for the web. But they are good at business strategy, know how to talk and how to use buzz words etc. The article is called "Six ways to make web 2.0 work" which is not really buzz word style, more short and catchy like you find on the web. A little too sales pitchy for my liking, anyway.
What is interesting is that they talk about ERP, then CRM as the previous types of tools that companies would be interested in using and implementing. This before the web 2.0 tools appeared. They are presenting web 2.0 systems as tools which are going to replace ERP and CRM tools as we know them.
And finishing off the article with a "Keep the conversation going on Twitter" (oh yes they are good with the buzz words)...
The article is well worth reading and provides numerous counter examples to the mainstream web 2.0 approach of "build it and they will come". I have often found that people who really take time to think a product through, test it and make it work for the final user(s), do succeed in producing great web sites...
The important part of the article covers what McKinsey describes as the 6 recommendations:
1. The transformation to a bottom-up culture needs help from the top.
2. The best uses come from users—but they require help to scale.
3. What’s in the workflow is what gets used.
4. Appeal to the participants’ egos and needs—not just their wallets.
5. The right solution comes from the right participants.
6. Balance the top-down and self-management of risk.
I question the reliability and accuracy of Generative AI (GenAI) in enterprise scenarios, particularly when faced with adversarial questions, highlighting that current Large Language Models (LLMs) may be data-rich but lack in reasoning and causality. I would call for a more balanced approach to AI adoption in cases of assisting users, requiring supervision, and the need for better LLM models that can be trusted, learn, and reason.
I discuss my experience with chatbots, contrasting older rules-based systems with newer GenAI (General Artificial Intelligence) chatbots. We cannot dismiss the creative capabilities of GenAI-based chatbots, but these systems lack reliability, especially in customer-facing applications, and improvements in the way AI is structured could lead to a "software renaissance," potentially reducing society's technical debt.
The article discusses the contrasting debate on how AI safety is and should be managed, its impact on technical debt, and its societal implications.
It notes the Center for AI Safety's call for a worldwide focus on the risks of AI, and Meredith Whittaker's criticism that such warnings preserve the status quo, strengthening tech giants' dominance. The piece also highlights AI's potential to decrease societal and technical debt by making software production cheaper, simpler, and resulting in far more innovation. It provides examples of cost-effective open-source models that perform well and emphasizes the rapid pace of AI innovation. Last, the article emphasises the need for adaptive legislation to match the pace of AI innovation, empowering suitable government entities for oversight, defining appropriate scopes for legislation and regulation, addressing ethical issues and biases in AI, and promoting public engagement in AI regulatory decisions.
Japan has made its ruling on the situation between Content creators and Businesses. Japanese companies that use AI have the freedom to use content for training purposes without the burden of copyright laws. This news about the copyright laws in Japan reported over at Technomancers is seen as Businesses: 1 / Content Creators: 0 The […]