Center for Medical Data Science, Medical University of Vienna.
Complexity Science Hub Vienna, Austria.
Perspect Psychol Sci. 2024 Sep;19(5):735-748. doi: 10.1177/17456916231185057. Epub 2023 Jul 19.
On digital media, algorithms that process data and recommend content have become ubiquitous. Their fast and barely regulated adoption has raised concerns about their role in well-being both at the individual and collective levels. Algorithmic mechanisms on digital media are powered by social drivers, creating a feedback loop that complicates research to disentangle the role of algorithms and already existing social phenomena. Our brief overview of the current evidence on how algorithms affect well-being, misinformation, and polarization suggests that the role of algorithms in these phenomena is far from straightforward and that substantial further empirical research is needed. Existing evidence suggests that algorithms mostly reinforce existing social drivers, a finding that stresses the importance of reflecting on algorithms in the larger societal context that encompasses individualism, populist politics, and climate change. We present concrete ideas and research questions to improve algorithms on digital platforms and to investigate their role in current problems and potential solutions. Finally, we discuss how the current shift from social media to more algorithmically curated media brings both risks and opportunities if algorithms are designed for individual and societal flourishing rather than short-term profit.
在数字媒体上，处理数据和推荐内容的算法已经无处不在。它们的快速采用，且几乎没有受到监管，这引发了人们对其在个人和集体层面上对幸福感的影响的担忧。数字媒体上的算法机制受到社会驱动因素的驱动，形成了一个反馈循环，这使得研究工作变得复杂，难以厘清算法和已存在的社会现象的作用。我们简要概述了当前关于算法如何影响幸福感、错误信息和两极化的证据，表明算法在这些现象中的作用远非简单明了，需要进行大量进一步的实证研究。现有证据表明，算法主要是在强化现有的社会驱动因素，这一发现强调了在包含个人主义、民粹主义政治和气候变化的更大社会背景下思考算法的重要性。我们提出了具体的想法和研究问题，以改进数字平台上的算法，并研究它们在当前问题和潜在解决方案中的作用。最后，我们讨论了如果算法的设计是为了个人和社会的繁荣而不是短期利润，那么当前从社交媒体向更具算法策划的媒体的转变既带来了风险，也带来了机会。
