House Science Chair Continues His War on Global Warming
Harassment seems to be the way that Lamar Smith challenges those who disagree with his views that climate change is not a problem. He has already subpoenaed NOAA head Kathryn Sullivan and followed this up complaints that he is not receiving the documents he requested promptly.
Harassment seems to be the way that Lamar Smith challenges those who disagree with his views that climate change is not a problem. He has already subpoenaed NOAA head Kathryn Sullivan and followed this up complaints that he is not receiving the documents he requested promptly. He wants to see all communications containing words such as “change” “Paris” “climate” and “UN” as well as those containing the name and location of the President.
The Union of Concerned Scientists fears what this may lead to and have told him his requests are aggressive and overly broad. There are concerns that he is trying to limit the work of many of the federal scientists. They site the request for documents with the words “buoy” and “temperature” as few items of correspondence will not contain one of these words. The actions he is taking are seen to be unjustified as well as unprecedented and has an adverse impact on many of the scientists who are taken away from the work they are supposed to be doing to sieve through documents.
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It is not understood why this path is being taken, rather than other scientists being asked to conduct their research – and why is it the chairman of the House Science, Space and Technology committee that is carrying out the harassment. Some believe, it could be connected to the fact that the fossil fuel industry gives $600,000 to Smith’s campaign fund.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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