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Trust in Scientists: A Global And Cypriot Perspective On Public Confidence

A recent global study, covering 68 countries including Cyprus and Greece, sheds light on the high levels of public trust in scientists and the widespread desire for their increased involvement in shaping societal and policy decisions. Published in Nature Human Behaviors, the research surveyed 71,922 individuals, offering the most detailed snapshot of global trust in scientists since the COVID-19 pandemic. The average global trust rating was 3.62 out of 5, reflecting a generally positive perception of scientists, though regional differences exist:

Countries With the Highest Trust

Egypt tops the list with a score of 4.30, followed by India, Nigeria, Kenya, and Australia.

Countries With the Lowest Trust

At the bottom, Albania ranked lowest with a score of 3.05, closely followed by Ethiopia, Russia, Bolivia, and Kazakhstan.

Greece And Cyprus

Greece ranks 56th with a trust rating of 3.39, just below the global average, while Cyprus follows closely with a slightly higher score of 3.42, placing 52nd in the global rankings.

The findings suggest that a significant portion of the public views scientists as competent (78%), honest (57%), and concerned about the welfare of society (56%). Furthermore, the study reveals that 75% of respondents agree that scientific methods are the most reliable means of discovering truth. More than half of the participants (52%) also believe that scientists should have a more direct role in policymaking.

Key Areas For Scientific Research Focus

The survey indicates that the public wants scientific efforts to concentrate on:

  • Enhancing public health
  • Addressing energy challenges
  • Alleviating poverty

On the other hand, there is a clear reluctance to prioritize military and defense technology, with many participants feeling that current research in these areas is overemphasized.

While trust in scientists remains strong, only 42% of respondents believe scientists actively consider public opinions. Additionally, 83% of participants called for improved communication between the scientific community and the public, as many feel that scientific priorities don’t always reflect societal needs.

Copyright Law Struggles To Keep Up With AI Training

Courts Are Still Applying Old Copyright Rules To AI

AI companies train models on enormous amounts of published material, including books, articles and academic research. Whether using that content without authors’ permission violates copyright law remains unresolved.

Much of the debate centres on fair use, which allows copyrighted material to be used without permission in certain circumstances. Courts consider factors such as the purpose of the use, how much material was involved and its impact on the original market.

Anthropic Case Sets An Important Precedent

A major case involving Anthropic and a group of authors provided one of the clearest rulings so far. Judge William Alsup found that using copyrighted books to train AI models was lawful, comparing the process to people reading and studying literature before creating something new.

Anthropic was nevertheless ordered to pay $1.5 billion in a settlement. The penalty concerned books the company had obtained from illegal online libraries rather than the AI training itself.

For AI companies, that distinction could prove significant because it separates studying copyrighted material from directly copying it.

Competition Could Be The Key Issue

A case involving Thomson Reuters and Ross Intelligence offers a different perspective. A court ruled that Ross could not claim fair use after using Reuters’ copyrighted material to develop a competing AI-powered legal research platform.

The decision suggests courts may be less willing to consider AI training fair use when copyrighted content is used to build a product that directly competes with the original.

For authors, an unresolved question is whether AI-generated content should be considered competition for the works used to train these models.

The Law Has Yet To Catch Up

US copyright law predates generative AI by decades, leaving courts to apply old principles to new technology. Questions also remain over copyright protection for AI-generated works. In Thaler v. Perlmutter, a court ruled that material created entirely by AI cannot receive copyright protection.

Major AI companies remain involved in copyright litigation, and different courts could reach different conclusions. For now, there is no universal rule: the legality of AI training will depend on the circumstances of each case and how courts ultimately interpret copyright and fair use.

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