IEEE Spectrum 09月12日
电子健康记录互操作性不足导致严重问题
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

美国电子健康记录(EHR)20年的推广忽视了互操作性,导致数以千计的医疗保健提供者面临昂贵、设计不良且不安全的系统,加剧了医护人员倦怠,造成数十亿美元的医疗记录丢失,并引发了新的医疗错误。政府为加速采用而做出的短视决策忽视了长期成本,其口号是“系统在互操作之前需要先运行”。这种“系统性反噬”——因加速技术采用而不考虑更广泛影响而导致的重大负面后果——在人工智能的全球部署中也可见一斑。人工智能公司CEO承认AI可能在未来五年内摧毁一半入门级白领工作,并将失业率推高至10至20%。然而,他们只关注AI的潜在好处,如治愈癌症、每年增长10%的经济和平衡联邦预算,却将失业问题推给他人解决。

🔍美国电子健康记录(EHR)20年的推广忽视了互操作性,导致数以千计的医疗保健提供者面临昂贵、设计不良且不安全的系统,加剧了医护人员倦怠,造成数十亿美元的医疗记录丢失,并引发了新的医疗错误。

📉政府为加速采用而做出的短视决策忽视了长期成本,其口号是“系统在互操作之前需要先运行”,这种“系统性反噬”——因加速技术采用而不考虑更广泛影响而导致的重大负面后果——在人工智能的全球部署中也可见一斑。

🤖人工智能公司CEO承认AI可能在未来五年内摧毁一半入门级白领工作,并将失业率推高至10至20%,但他们只关注AI的潜在好处,如治愈癌症、每年增长10%的经济和平衡联邦预算,却将失业问题推给他人解决。

📉杀死当前的生态系统意味着AI将越来越多地摄入由其他AI编写的新内容,因为生产内容的那些人类已经消失或即将消失,导致“垃圾进,垃圾出”,最终影响所有人。

🔍这种“系统性反噬”不仅限于医疗和就业领域,它提醒我们在推广任何新技术时都必须考虑更广泛的影响,否则负面后果最终会波及所有人。



One of the most sobering insights from Contributing Editor Robert N. Charette’s feature story in this issue is that the 20-year rollout of electronic health records (EHRs) in the United States happened with an intentional disregard for interoperability. As a result, thousands of health care providers are “burdened with costly, poorly designed, and insecure EHR systems that have exacerbated clinician burnout, led to hundreds of millions of records lost in data breaches, and created new sources of medical errors,” Charette writes.

The U.S. government made this myopic decision in order to speed up EHR adoption, ignoring the longer-term costs. The operating mantra, says Charette, was that EHR systems “needed to become operational before they could become interoperable.”

You could call what happened next “unintended consequences,” but that would absolve decision-makers in government and industry for making choices they knew could compromise user experience, security, and patient outcomes. The results were entirely foreseeable. A more appropriate term might be “systemic blowback”—large-scale negative outcomes that result from decisions to accelerate the adoption of new technology without consideration for the broader potential impacts.

Once you see systemic blowback in one technological context, you start to see it in others. Case in point: the global deployment of artificial intelligence.

AI’s Impact on White-Collar Jobs

In May, Dario Amodei, CEO of Anthropic, maker of Claude AI, told Axios that AI could wipe out half of all entry-level white-collar jobs—and spike unemployment to 10 to 20 percent in the next one to five years. (U.S. unemployment was about 4 percent in June.) “We, as the producers of this technology, have a duty and an obligation to be honest about what is coming,” Amodei said. “I don’t think this is on people’s radar.”

But Amodei’s acknowledgment of the potential harms of mass AI adoption comes off as just virtue signaling. Big AI, Amodei surmises, will continue to develop this technology so we can cure cancer, grow the economy 10 percent annually, and even balance the federal budget. And by the way, up to one in five people will soon be unemployed. That last part—the harm—is someone else’s problem to solve.

Computer programmers are feeling the harm right now. According to The Washington Post, more than a quarter of all coding jobs have vanished in the last two years, with much of that loss attributable to AI usage. As Spectrum reported last month, LLMs are improving at an exponential rate, which doesn’t augur well for the rest of the human workforce.

“Systemic blowback”—large-scale negative outcomes that result from decisions to accelerate the adoption of new technology without consideration for the broader potential impacts.

That includes people working in media. Ever since Google emerged as the home page of the Web in the early 2000s, media outlets operated under the assumption that Google would reliably crawl their sites and send audience their way.

Google blew up that deal when it introduced AI answers to its entire user base earlier this year. Since then, Spectrum has had about double the impressions—the times Spectrum content shows up on the search results page or, increasingly, in an AI answer—and about 40 percent fewer click-throughs from people coming to our website to read the cited article. As Web traffic dies, so do the business models predicated on that traffic. Oh well, says Big AI, someone else’s problem.

But killing off the current information ecosystem means that AIs will increasingly ingest new content written by other AIs, because the humans who produced the content are gone or will be soon. Garbage in, garbage out. This time next year, don’t be surprised when your shiny, new AI agent gives you a morning briefing that’s just off. Then Big AI’s problem will be your problem. Sooner or later you too will feel the systemic blowback.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

电子健康记录 互操作性 系统性反噬 人工智能 就业影响 医疗错误 技术风险
相关文章