Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Large language models are fundamental technologies used in interfaces like ChatGPT and are poised to change the way people access and make sense of health information. The speed of uptake and investment suggests that these will be transformative technologies, but it is not yet clear what the implications might be for health communications. In this viewpoint, we draw on research about the adoption of new information technologies to focus on the ways that generative artificial intelligence (AI) tools like large language models might change how health information is produced, what health information people see, how marketing and misinformation might be mixed with evidence, and what people trust. We conclude that transparency and explainability in this space must be carefully considered to avoid unanticipated consequences.
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Source |
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http://dx.doi.org/10.1080/17538068.2023.2277489 | DOI Listing |