Anthropic CEO Amodei refutes criticism of "pessimism", saying that the root cause of the trust crisis in AI is unfulfilled promises. As public discussions around AI risks and regulation continue to heat up, Anthropic CEO Dario Amodei recently publicly refuted outside criticism that he "delivered an overly pessimistic picture."

Anthropic CEO Amodei refutes criticism of "pessimism", saying that the root cause of the trust crisis in AI is unfulfilled promises. As public discussions around AI risks and regulation continue to heat up, Anthropic CEO Dario Amodei recently publicly refuted outside criticism that he "delivered an overly pessimistic picture." This response directly refers to investor Gavin Baker’s remarks on the All-In podcast and social platform Amodei denies that its messaging has a negative slant, stressing that its article "Loving Machines" was designed to "balance risks and benefits" and was originally intended to make up for the industry's lack of portrayal of technology's potential to improve the world. He acknowledged that the public has a generally negative view of AI and that this is a major problem, but firmly denied that this sentiment was mainly due to his or other leaders' warnings about risks, and attributed it to "a fundamental crisis of trust" - the public's long-term lack of trust in business and government, and the AI ​​rebound is only the latest manifestation of this deep contradiction. Regarding external criticism, Amodei admitted that companies such as Anthropic "have not fulfilled their grand promises to benefit the world" and that is the core issue that should be focused on, rather than propaganda rhetoric. He believes that tangible results such as curing cancer are far more powerful than slogans in reshaping public perception. In terms of regulatory stance, Amodei rejected the binary choice of “widespread vs. concentration of power” proposed by Baker, pointing out that regulation is often viewed by outsiders as a tool to check and balance corporate power. He revealed that Anthropic’s policy recommendations have always deliberately avoided provisions that benefit large frontier companies and instead supported small competitors because of their firm belief that AI structurally tends to concentrate power and that the open weight model cannot adequately address this problem. He believes that properly designed rules can simultaneously deal with the catastrophic risks of AI, institutionally restrain the power of cutting-edge companies, and reserve space for open weight models. via AI News (author: AI Base)