Reporting of screening and diagnostic AI rarely acknowledges ethical, legal, and social implications: a mass media frame analysis.

BACKGROUND: Healthcare is a rapidly expanding area of application for Artificial Intelligence (AI). Although there is considerable excitement about its potential, there are also substantial concerns about the negative impacts of these technologies. Since screening and diagnostic AI tools now have the potential to fundamentally change the healthcare landscape, it is important to understand how these tools are being represented to the public via the media. METHODS: Using a framing theory approach, we analysed how screening and diagnostic AI was represented in the media and the frequency with which media articles addressed the benefits and the ethical, legal, and social implications (ELSIs) of screening and diagnostic AI. RESULTS: All the media articles coded (n = 136) fit into at least one of three frames: social progress (n = 131), economic development (n = 59), and alternative perspectives (n = 9). Most of the articles were positively framed, with 135 of the articles discussing benefits of screening and diagnostic AI, and only 9 articles discussing the ethical, legal, and social implications. CONCLUSIONS: We found that media reporting of screening and diagnostic AI predominantly framed the technology as a source of social progress and economic development. Screening and diagnostic AI may be represented more positively in the mass media than AI in general. This represents an opportunity for health journalists to provide publics with deeper analysis of the ethical, legal, and social implications of screening and diagnostic AI, and to do so now before these technologies become firmly embedded in everyday healthcare delivery.

Filling the gap between evidence, policy and practice: are 45 and Up Study researchers planning for impact?

AIM: To improve health outcomes, policy and practice decisions should be guided by relevant and timely evidence. High-quality, large-scale population data could play an essential role in supporting evidence-based decision making. The 45 and Up Study is a long-term, large-scale cohort study with more 250 000 participants aged 45 years and over from New South Wales (NSW), Australia. Data collected by the Study is accessible to researchers, government and non-governmental bodies. The study aimed to identify the proportion of researchers using data from the Study who intended to have an impact and achieved impact; the types of impact they intended and achieved; and the pathways through which they achieved it. METHODS: Using data extracted from the application, progress and final report documents for 25 projects using 45 and Up Study data from January 2011 until December 2017, we a) determined the proportion of projects that intended to have policy or practice impact and b) described the type of policy and practice impact achieved. RESULTS: We found that 88% (n = 22) of projects intended to have a policy or practice impact. Of those, 68% (n = 15) planned to influence or inform a policy or program, and 41% (n = 9) planned to share findings at conferences or in journals. Almost half of projects with intended impact (45%, n = 10) did not state how they planned to achieve impact. Approximately 16% of all projects (n = 4) reported achieving an impact on policy or services. The type of impact achieved by all four of these projects was influencing, informing or changing a policy or program. One of these four projects also achieved a change to legislation or regulation. CONCLUSIONS: Further strategies to promote a targeted approach to impact planning in research projects using datasets such as the 45 and Up Study would help guide researchers in achieving impact.