Following an analysis of existing AI-related exchange-traded funds (ETFs), we reveal the selection criteria for determining which stocks qualify as AI-related are often opaque and rely on vague phrases and subjective judgments. This paper proposes a new, objective, data-driven approach using natural language processing (NLP) techniques to classify AI stocks by analyzing annual 10-K filings from 3,395 NASDAQ-listed firms between 2011 and 2023. This analysis quantifies each company's engagement with AI through binary indicators and weighted AI scores based on the frequency and context of AI-related terms. Using these metrics, we construct four AI stock indices-the Equally Weighted AI Index (AII), the Size-Weighted AI Index (SAII), and two Time-Discounted AI Indices (TAII05 and TAII5X)-offering different perspectives on AI investment. We validate our methodology through an event study on the launch of OpenAI's ChatGPT, demonstrating that companies with higher AI engagement saw significantly greater positive abnormal returns, with analyses supporting the predictive power of our AI measures. Our indices perform on par with or surpass 14 existing AI-themed ETFs and the Nasdaq Composite Index in risk-return profiles, market responsiveness, and overall performance, achieving higher average daily returns and risk-adjusted metrics without increased volatility. These results suggest our NLP-based approach offers a reliable, market-responsive, and cost-effective alternative to existing AI-related ETF products. Our innovative methodology can also guide investors, asset managers, and policymakers in using corporate data to construct other thematic portfolios, contributing to a more transparent, data-driven, and competitive approach.

As part of a broader look at the impact of generative AI, this study investigated the emotional responses of journalists to the release of ChatGPT at the time of its launch. By analyzing nearly 1 million Tweets from journalists at major U.S. news outlets, we tracked changes in emotional tone and sentiment before and after the introduction of ChatGPT in November 2022. Using various computational and natural language processing techniques to measure emotional shifts in response to ChatGPT's release, we found an increase in positive emotion and a more favorable tone post-launch, suggesting initial optimism toward AI's potential. This research underscores the pivotal role of journalists as interpreters of technological innovation and disruption, highlighting how their emotional reactions may shape public narratives around emerging technologies. The study contributes to understanding the intersection of journalism, emotion, and AI, offering insights into the broader societal impact of generative AI tools.

Helen Toner, one of OpenAI's former board members who was responsible for firing CEO Sam Altman last year, revealed that the company's board didn't know about the launch of ChatGPT until it was released in November 2022. "[The] board was not informed in advance of that," Toner said on Tuesday on a podcast called The Ted AI Show. "We learned about ChatGPT on Twitter." Toner's comments came just two days after criticized the way OpenAI was governed in an Economist piece published on Sunday that she co-wrote with Tasha McCauley, another former OpenAI board member. This is the first time that Toner has spoken openly about the circumstances that led to Altman's dramatic ouster from the company he co-founded in 2015, and his quick reinstatement following protests from employees.

Bard is a descendant of an earlier language model of Google's called Lamda, which was never fully released to the public. It did, however, attract a lot of attention when one of the engineers who worked on it claimed its answers were so compelling that he believed it was sentient. Google denied the claims and he was fired.