Both Bias and Safety Teams are at Each Other’s Throat over AI



Academia two research teams at AI labs & Some are working to prevent AI dangers

Artificial intelligence systems are getting more and more impressive. Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. AI solutions are being developed that have the potential to mitigate biases and, as a result, enable more diverse and inclusive workplaces. From the development of self-driving cars to the proliferation of smart assistants like Siri and Alexa, AI is a growing part of everyday life. Nowadays having problems with AI ethics, AI data privacy, AI bias, and problems of AI alignment. AI poses present risks and future ones.

The research team in academia at major AI labs these days working on the problem of AI ethics. And the research team in academia that is working on the problem of AI alignment. Today, that often means that AI ethicists and those in AI alignment are working on similar problems. AI alignment is just the problem of AI bias. Artificial intelligence is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.

Both Bias and Safety Teams:

Academia research team at major AI labs these days working on the moral concerns raised by AI systems specially focused on data privacy concerns and on what is known as AI bias that, using training data with bias often built in, produces racism and refusing women credit card limits, etc. And another academic research team is working on the problem of AI alignment that, as our AI systems become more powerful, our oversight methods and training approaches will be more and more.

Improving the understanding of the AI systems is one approach to solving AI alignment. It has handed humanity’s future over to systems with goals and priorities. Additionally, it is crucial for understanding when and where models are being misleading or discriminatory. Right now AI systems are, in a sense stupid. But AI won’t stay stupid forever, because lots of people are working diligently to make it as smart as possible.

AI can cause harm, they mostly do so either by replicating the harms in the data sets used to train or by deliberate misuse by bad actors. Several research teams are working to train AI models that do have a good understanding of the world. AI ethics academia AI labs research team focused on managing the implications of modern AI, and AI alignment academia at some research team focused on preparing for powerful future systems.