Ford v Ferrari to ChatGPT v Bard
The primary drivers of AI advancements right now are not addressing user needs or information access problems; they are, rather, driven by competition.
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The primary drivers of AI advancements right now are not addressing user needs or information access problems; they are, rather, driven by competition.
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ChatGPT is a simple-to-use conversation agent developed by OpenAI. Of course, this is not the first time we have seen an AI agent that generates information. Google’s LaMDA and Meta’s Galactica are some recent examples for text generation.
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Many AI systems, especially those generating texts and images are starting to give an impression that they understand and even feel things. This illusion create misinformation and misdirection.
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Preserving and presenting information has gone through several models in our history. For the most part, information access has been considered a public good. It is only in the recent decades that we have seen the emergence of profit-driven models. And it’s time we question that model.
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Information Matters started developing a year ago. I took that opportunity to reflect on last 75 years of development of ideas in the areas of information science and technology. A year later now, I’m looking back at what Information Matters has been able to do to push the envelop with ideas, opinions, and outcomes for charting a new era of information that matters.
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There is much too hype around AI systems that are acting like they know or feel. But we are not asking enough if we should even want such systems. Blindly trusting systems that make us believe as if they understand us or know everything can be dangerous.
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Do you have a favorite “third place” to hang out? A place that’s other than your home and work? With the ongoing pandemic, we have lost that place, but that virtual or physical place is so important that we need to rediscover and reintroduce it in our lives.
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We all want fairness in our lives. We want to everyone to pay their fair share, get a fair shot at opportunities, and provide fair explanations to life-changing decisions. But what we can’t agree on is what is this fairness and how to implement it in everyday systems we use.
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We are giving up more and more agency and control to AI systems as we build more trust in them. But there are dangers to doing so—both for the users and the systems. We need a better understanding of this trust and the inner workings of the systems to create a sustainable future.
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We are addicted to online information access, devices, and services. Breaking away from this addiction is not going to be easy, but we can learn some lessons from how we changed our tobacco consumption behavior over decades.
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