There has been growing concerns around the risks of open source AI. In the recent past these have begun to manifest themselves in the form of export restrictions on open source AI models - that could have a deleterious effect on India’s AI strategy.
Artificial intelligence might eventually replace us. But it still has a long way to go. In the meantime, rather than fretting about what might be, we should learn to use it so that we can make the most of all the efficiencies it offers. Here is how I do that.
We tend to resist change. We worry about the ways in which it could alter our existing way of life and the harms that could result as a consequence. But these technological changes almost always end up being nowhere near as frightening as they first seemed.
We need to encourage a culture of failure around AI so that when it fails we can understand why and disseminate those learnings throughout the industry. It is only when we can fail without fear that we will learn to do what it takes to build safe AI systems.
The PM-EAC suggests that AI should be regulated as a complex adaptive system. While there is a lot to say about this approach, in its articulation, the paper fails to take into account many of the essential features of modern AI.
There is widespread consternation around the impact that deep-fakes are going to have on all of society this year. But most legislative counter-measures are oriented towards shooting the messenger. We need a different path. Thankfully we have been here before.
In the last week of 2023, the New York Times sued OpenAI and Microsoft for copyright infringement. The allegations in the complaint go to the core of how generative AI works and could shape the manner in which AI works going forward.
2023 was the year in which DPI assumed its rightful place on the world stage. It was also the year in which artificial intelligence came into its own. There has never been a more interesting time to be engaged in technology policy.
The European Union has agreed to a new law to regulate artificial intelligence (AI) by imposing transparency requirements on general AI models and stronger restrictions on more powerful models. The US offers a broader, more nuanced framework. However there exists a North-South divide - with the Global South viewing AI as beneficial as contrasted to the more risk-focused approach of the Global North.
When man invented writing he enabled the creation of a hive-mind that eventually lead to the establishment of civilisation as we know it. The advent of large language models has exponentially expanded that hive-mind but has it done so at the cost of our humanity?
