人工智能医疗的三个逻辑

人们对人工智能医疗的发展普遍持乐观态度,仅有少数研究从数据相关的角度对其负面效应表示了谨慎的担心。研究回顾了支撑人工智能医疗发展的技术和市场逻辑指出,是冷战竞赛和经济衰退等历史偶然性导致了人工智能医疗对以错误率为代表的“客观”结果和市场规模、收购金额以及医院成本收益等“主观”价值的片面关注。但以“黑箱化”的方式忽略社会逻辑,尤其是对医疗体制尚不成熟的中国而言,不可避免地会引发专业人才缺口进一步加剧、优质医疗资源进一步集中,以及缺医少药的部分人群始终被排除在新技术的美好蓝图之外等一系列的严重后果。     

情绪预测偏差的成因及干预

情绪预测偏差是一种对未来事件发生时情绪反应的预测和实际体验之间的分离现象。梳理该领域最近10年(2009~2019年)研究文献可知, 热点研究主题涉及偏差的现象、成因和干预, 相应呈现为三点主要发现: 情绪预测偏差十分普遍, 情绪预测偏差成因多源, 情绪预测偏差可以干预。未来研究应着力关注情绪预测偏差的发生模式和心理机制, 着力揭示具体偏差的神经心理机制, 并从进化和文化视角综合考察偏差的发生机制。     

青少年情绪预测偏差与决策的关系研究

在决策过程中人们通常选择那些使其感到快乐的行为,决策结果与所预测的高兴或悲伤、满意或不满意紧密相连,以往研究发现这类预测即情绪预测存在偏差。本研究以188名中小学生为被试,采用自编情绪评定表和最后通牒游戏范式,对情绪预测偏差与决策的关系进行探索。结果表明青少年在预测对未来事件的情绪反应时存在强度偏差和持续时间偏差,情绪预测的强度偏差和持续时间偏差影响青少年回避或趋向决策。     

身体的技术构建及其道德维度

当代生命科技在拓展身体的功能空间,使身体的功能得以延伸的同时,也日益渗透到身体的内部,并成为身体的一部分,技术与身体的交互作用是一个双向建构的过程,一方面,人按照自己身体的需要使技术表现出适合身体需要的人文性;另一方面,技术又以现实的存在影响人的价值、目标。身体在被技术异化的同时,也在一定程度上引导着技术,使技术依身体的需要而发展。技术对身体的异化和控制必须与人类文化和技术与境相适应,以维护人的尊严和自我存在为前提,恪守技术伦理的底线,遵循基本的道德共识。

     

对医学技术的控制何以可能——兼谈应对医学技术主体化的策略

医学科技的价值负载、医学技术的主体化趋势以及医学技术应用的不确定性要求人们必须对医学科技的发展进行控制,技术控制主义思潮为此提供了可资借鉴的宝贵思想资源;而技术的社会形成论与技术独立性的限度确证了对技术进行控制的可能性。对医学技术进行控制主要有技术手段和社会手段,采取技术手段必须防止盲目乐观主义陷阱;采取社会手段则必须妥善应对斯诺难题,实现医学技术和医学人文的有机融合。同时,要充分发挥政府调控在医学技术控制中的作用。     

损失规避源于得失程数多于获得？——损失规避的得失程数变化视角的再检验

刘欢、梁竹苑 和 李纾（2009a）在证明损失规避的得失程数变化视角时所取的损益值取值范围、对安于现状偏差影响的控制以及所选取的得两程失一程和得三程失两程的决策对象这四个方面存在的缺陷。本研究通过弥补上述缺陷并设计无关变量得到更严格控制的得三程失两程的决策情景,对得失程数变化视角重新进行了检验。结果发现,寿命“得一程失一程”的属性并未导致损失规避消失;在广泛的损益值范围内以自由为对象的决策同样表现为损失规避;将自由感知为生而拥有和后天获得的人数大致相当;因而得失程数变化视角需作出重要修正,同时前景理论与情绪预测误差理论亦不可完全预测损失规避出现的条件。     

Preference for human or algorithmic forecasting advice does not predict if and how it is used

Past research has found that people treat advice differently depending on its source. In many cases, people seem to prefer human advice to algorithms, but in others, there is a reversal, and people seem to prefer algorithmic advice. Across two studies, we examine the persuasiveness of, and judges' preferences for, advice from different sources when forecasting geopolitical events. We find that judges report domain-specific preferences, preferring human advice in the domain of politics and algorithmic advice in the domain of economics. In Study 2, participants report a preference for hybrid advice, that combines human and algorithmic sources, to either one on it's own regardless of domain. More importantly, we find that these preferences did not affect persuasiveness of advice from these different sources, regardless of domain. Judges were primarily sensitive to quantitative features pertaining to the similarity between their initial beliefs and the advice they were offered, such as the distance between them and the relative advisor confidence, when deciding whether to revise their initial beliefs in light of advice, rather than the source that generated the advice.     

Data-Informed Advances and Technology Augmentation

The augmentation of technology to the delivery of CBT has enormously increased in recent years. This commemoration of Dr. Aaron T. Beck’s contribution to the field focuses on examples such as CBT internet treatments, video treatments, but especially on data-informed CBT, precision mental health and digitally based treatment navigation systems. It ends with an outlook on continuous outcome measurement as the basis for a broader understanding of clinical concepts and data-driven clinical practice in the future.     

Expecting tasks to help or hurt subsequent cognitive performance: Variability,accuracy, and bias in forecasted after-effects

After-effects on cognition—where a prior activity either benefits or hinders subsequent cognitive performance—are empirically inconsistent. Do people have insight into when their subjective energy and cognition will be helped or hurt by engaging in prior activities? Studies 1a and 1b (combined N  =  316) find that people expect more demanding and unenjoyable tasks to hinder their subsequent energy and cognitive performance, regardless of their willpower lay theory. Study 2 (N  =  167) examines the accuracy of these forecasts using a within-subject design. Participants’ forecasts of their future subjective states did predict their actual experienced subjective states, but participants were not able to accurately forecast their subsequent maths performance. Additionally, they significantly overestimated the detrimental effects of demanding prior activities on both subjective state and performance. Study 3 (N  =  210) found that participants’ overestimation of detrimental after-effects could result in unnecessary financial costs, suggesting these biased forecasts can have consequences.