Literature Review

When using AI leads to “brain fry”Harvard Business Review; by Julie Bedard, Matthew Kropp, Megan Hsu, Olivia T. Karaman, Jason Hawes, Gabriella Rosen Kellerman; 3/5/26A new study finds that certain patterns of AI use are driving cognitive fatigue, while others can help reduce burnout... Firms are incentivizing employees to build and oversee complex teams of agents—for example, by measuring and rewarding token consumption as a proxy for performance. Meta, for one, includes the number of lines of code generated by AI as a performance metric for engineers. As enterprises use more multi-agent systems, employees find themselves toggling between more tools. Contrary to the promise of having more time to focus on meaningful work, juggling and multitasking can become the definitive features of working with AI... The literature is filled with mixed signals on the relationship between AI and worker burnout. (Burnout is as a state of chronic workplace stress consisting of exhaustion, negative feelings about work, and decreased effectiveness on the job.) Some studies suggest that using AI to replace tiring tasks alleviates exhaustion; other studies, sometimes on the same populations, show AI use worsening burnout outcomes... This highlights the subtle-but-important distinction between the types of stress that AI can alleviate, and those that it may worsen. Our findings are both a guide and a warning.

AI and healthcare: Bob WachterGeriPAL podcast; Alex Smith, Eric Widera, Bob Wachter; 2/5/26Today we interviewed Bob Wachter about his book, “A Giant Leap: How AI Is Transforming Healthcare and What That Means for Our Future.” You may recall we interviewed Bob in April 2024 about AI, and at that time he was on the fence about AI – more promise or more peril for healthcare? As his book’s title suggests, he’s come down firmly on the promise side of the equation.

"Black box" artificial intelligence for mortality prediction: a mixed- methods study of palliative care team, patient, and caregiver perspectives Annals of Palliative Medicine; by Beatrice Bridge, Ahmed Y Alasmar, Lauren Gunn-Sandell, Regina M Fink, Stacy M Fischer, Elizabeth Juarez-Colunga, Eric G Campbell, Matthew DeCamp; 2/26/26 Background: New artificial intelligence (AI)-based mortality prediction algorithms could support both patients' prognostic awareness and person-centered palliative care. ... Results: Among 53 interviewees, 18 expressed only concern about black box AI-based prognostication, 17 expressed only unconcern, and 18 interviewees expressed mixed sentiments. Reasons for concern related to: data transparency, mistrust of machines or their creators, patient-clinician communication, bias, and accuracy. Reasons for unconcern related to: inexplicability not unique to AI, greater accuracy, not using AI in isolation, trust in science, and being evidence-based. Notably, "accuracy" and "trust" appeared in both.

Let's talk about robotics in nursingHealth Leaders; by G Hatfield; 3/2/26... CNOs who want to incorporate robotics into nursing workflows must focus on adapting care models and staffing to maintain quality and continuity. According to Wills, staffing models may shift towards stronger roles in pre-admission testing, nurse navigation, virtual check-ins, and ambulatory recovery support. "I think CNOs need to think beyond the walls of the hospital, and this means redesigning care models that emphasize preoperative education, care coordination, and postoperative discharge follow-ups," Wills said.Editor's Note: Is this a wave of the future? Typically, hospice organization's join healthcare's technology later rather than sooner. Values of "humanity," "empathy," and "compassion" take precedence. This article is posted for your awareness. What are potential settings? Uses? Pro's and con's? Implications for care with persons experiencing dementia? More questions abound.

AI in healthcare needs system-level execution, not task automation Becker's Health IT; by Aditya Bansod; 2/18/26 Healthcare is investing in AI. But most operating models haven’t changed. Health systems have long had more manual work to do than staff to perform it. Now, these health systems are rapidly adopting AI under the promise that it will take on more autonomous work and deliver outcomes at a greater scale than their previous digital initiatives. They’re piloting chatbots, deploying AI phone agents, testing predictive models, and moving clinical documentation to AI assistants. Yet in many organizations, the core operating structure remains reactive. ...

Artificial intelligence-powered predictive tools to improve end-of-life decision-making: mini-review British Medical Journal (BMJ) Supportive & Palliative Care; by Abdullah Alabbasi, Muhanad Alzahrani, Faris Sultan and Mohammed Sayes; 2/18/26 Results: ... Preliminary qualitative work indicates that AI-generated summaries may assist communication among healthcare teams, though concerns persist regarding transparency, bias and over-reliance on algorithms. Conclusions: AI-driven prognostic models show promise in improving risk identification and facilitating earlier engagement with palliative care. Nonetheless, the current evidence base is preliminary. Future research should include prospective trials and strengthened ethical frameworks to ensure that the integration of AI-based prognostic tools into end-of-life decision-making is both safe and equitable. 

Generative artificial intelligence in palliative care: A comparative evaluation of ChatGPT-4o and ChatGPT-5 as clinical decision support tools Digital Health; by Emre Vuraloglu, Kervansaray; 1/29/26 Conclusions: ChatGPT-5 demonstrated measurable improvements over ChatGPT-4o in key domains of palliative care symptom management, while maintaining consistently high ethical sensitivity. These findings provide the first systematic evidence of the potential of generative AI, with the updated ChatGPT-5 model released in August 2025, as a complementary and reliable clinical decision support tool in palliative care.

Not all AI is created equal Access Newswire, Hamden, CT: Press Release; 1/22/26 Not all AI in home health and hospice is created equal. Many AI solutions appear similar at first glance. They promise efficiency and reduced administrative burden. What separates them is the depth of industry knowledge behind the technology. That distinction matters. In other words, there is a big difference between a healthcare company creating technology and a tech company breaking into the healthcare industry. People matter in home health and hospice. That includes the people who make the tools you use. 

How to build an AI-augmented workforce: The CIO's guide TechTarget; by Kinza Yasar; 1/5/26 As artificial intelligence (AI) reshapes industries, forward-thinking CIOs are shifting their strategies from automation-first to augmentation-first. Their goal is to equip employees with AI tools that strengthen their judgment, spark creativity and boost productivity. In an AI-augmented workforce, humans and AI systems work collaboratively, not competitively. Rather than replacing employees, AI is used to enhance human capabilities, automate routine tasks and provide insights that help people make more informed decisions and focus on higher-value work. 

How businesses can empower employees to unlock AI’s true potential Training; by Sandra Loughlin, PhD; 1/6/26 When ChatGPT launched in November 2022, it began one of the most significant technological disruptions in the past several decades, on par with the Internet and personal computers.  ...  However, amid this AI gold rush, many business leaders failed to realize that they were sitting on one of the technology’s most powerful enablers (and barriers): people.

How to work clinically and ethically with chatbots and AI Medscape; by Arthur L. Caplan, PhD; 12/30/25 Hi. I’m Art Caplan. I’m at the Division of Medical Ethics at NYU Grossman School of Medicine in New York City. I’m getting an interesting question from many doctors from different specialties, and also from more primary care people. How do I work clinically and ethically with chatbots and artificial intelligence? They’re not asking about making appointments or handling data behind the scenes. They want to know, in dealing with patients, how do I do this and do this right? ...

Today’s cyberattacks may be too advanced for traditional antivirus protection Kenosha.com; by Mark Hoffman; 12/19/25 ... The cybersecurity landscape has fundamentally shifted, with endpoint devices now the primary targets of malicious actors seeking to infiltrate business networks. According to the FBI’s Internet Crime Complaint Center, businesses reported over $12.5 billion in losses from cyberattacks in 2023, representing a 22% increase from the previous year. Remote work has exponentially expanded the attack surface, creating millions of new endpoint vulnerabilities that traditional endpoint security tools struggle to monitor effectively.