The need for real, viable data in AI
Artificial intelligence (AI) is undeniably a hot technology at the moment, with the industry projected to be worth $22.6 billion by 2025. Over the past year, everyday people saw AI-generated images and filters across social media as well as Open AI’s tools, ChatGPT and DALL-E, explode seemingly overnight.
While AI shows significant signs of promise, it still has a long way to go before companies and consumers can seriously rely on it for important tasks. For example, ChatGPT is able to formulate text, but it is not advanced enough to be reliably accurate. The consumer publication, CNET, attempted to increase output by employing AI to write its articles, but the outlet has since issued massive corrections to its AI-written content.
At first glance, ChatGPT-making sloppy errors might not seem like the end of the world, but if we are going to leverage AI in life-or-death fields like medicine, it can’t afford to make any mistakes. To prevent catastrophe, leaders in the AI space need to collaborate with experts in other technology sectors to establish fail-safe methods to validate data and ensure that AI is providing accurate information.
AI is poised to disrupt the technological landscape and positively impact multiple industries, from blockchain and fintech to healthcare. If used with integrity, AI could be as transformational as the internet was in the early 2000s. AI is limited only by the algorithms we create, the data we provide, and computing power.
From predicting cancer risk to preventing insurance underwriting burnout, AI will transform how we gather information and make critical decisions. This emerging technology can even remove racial and gender bias, making the outcomes from employee recruitment more fair and
Read more on cointelegraph.com
