Designing sites is a great opportunity, especially when you are lucky enough to be surrounded by clever and experienced people. When you can combine extremely talented people at all the different levels you require to build a website the results can be amazing. Although traditional advertising agencies are starting to learn that they need to further integrate the technical implications of the production of a website into projects, user experience is just as important and often overlooked by so many agencies. Design is considered the Holy Grail but this can hide some ugly surprises when the user experience aspect of the website is overlooked. Experience architecture when used in a rigorous way can really help to understand what will help the end-users of a site will be looking for, how and where to include it in your website.
While reading an article on SearchEngineLand I was happy to see that the experience architecture aspect of a site build was nicely touched upon. First impressions count. It really does give you an extra insight into the way the site can be successful when you try to understand how people will react to a site, what they are looking for and how designing it differently can help you help them find what they are looking for quickly without compromising the design.
The gut feeling is an important factor with today's fast moving generation Z, the same gut feeling can be tested with various personas you have identified as your key target population to make sure that you don't alienate your other personas from previous generations.
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 […]