The world of the future is not the world of capitalism, it’s the world of ‘talentism.’
— Read on www.forbes.com/sites/joemckendrick/2021/01/29/the-great-digital-reset-chasing-talent-not-capital/
New Algorithms Could Reduce Racial Disparities in Health Care | WIRED
Machine learning programs trained with patients’ own reports find problems that doctors miss—especially in Black people.
— Read on www.wired.com/story/new-algorithms-reduce-racial-disparities-health-care/
Startup Opportunities In AI – The Unbundling Of Search
Search is unbundling into a huge wave of business opportunities- and it’s not just Google anymore.
— Read on www.forbes.com/sites/konstantinebuhler/2021/01/12/startup-opportunities-in-ai–the-unbundling-of-search/
Health IT execs offer thoughts on the big issues of 2021 | Healthcare IT News
Where are vaccine supply chains, value-based care, AI, telehealth and other trends headed next year? C-suite leaders from an array of vendors weigh in on provider/payer relations, the healthcare workforce and more.
— Read on www.healthcareitnews.com/news/health-it-execs-offer-thoughts-big-issues-2021
2021 could be the year automation and AI truly accelerate the economy – Axios
Productivity growth has been stagnant for years, but new technologies are finally set to change that.
— Read on www.axios.com/productivity-growth-j-curve-automation-ai-23bf33a3-ebf9-4407-9668-006db8984497.html
Bryan Walsh – Technology
The coronavirus pandemic hit the global economy hard in 2020, but the economy may be close to consolidating years of technological advances — and ready to take off in a burst of productivity growth.
Why it matters: Productivity is the engine that makes the economy grow for everyone. If long-gestating technologies like AI and automation really are ready to fulfill their potential, we’ll have the chance to escape the great stagnation that has choked our economy and poisoned our politics.
What’s happening: Hidden in part by the human and economic suffering of the pandemic, 2020 saw a collection of remarkable technological breakthroughs, including a mRNA vaccine for COVID-19 and advances in AI language generation.
Context: In a blog post published last month, the economist Tyler Cowen added in a few others, including affordable solar power and remote work, and asked whether total factor productivity (TFP) — a rough approximation of the effect technological and strategic progress has on economic productivity — in 2021 “will be remarkably high, maybe the highest ever?”
• Cowen’s musings matter because he literally wrote the book on “the great stagnation” — his term for the curious and persistent slowdown in wage and productivity growth in the U.S. over the past few decades, even as the internet and everything that grew out of it seemed to transform life as we knew it.
Flashback: After a few postwar decades of scorching growth, labor productivity began to decelerate sharply in the 1970s, and aside from a period of 3% growth in the mid-1990s to early 2000s — which economists attributed to the widespread effects of the computer — it’s stayed mired at about 1.2% a year ever since .
• Some experts have argued that conventional economic metrics fail to fully measure the productivity benefits of newer technologies like social media and the internet, but even so, they don’t compare to the advances of the past, like widespread electrification and antibiotics.
It looks increasingly possible that the last decade plus of sluggish productivity growth isn’t a sign that the benefits of new technology have permanently plateaued, but that businesses were using the time to invest in and adjust to those new advances — and that we may now be ready to reap the benefits.
• Economists like Erik Byrnjolfsson have argued that we’re experiencing a “productivity J-curve.”
• When powerful new technologies are introduced into the economy, productivity may flatten or even dip a bit as initial investments are made — the first part of the J. But once those technologies have been fully digested, productivity can swoop upwards — the second part of the J.
• That’s what we’ve seen in the past. Computers began to filter into the workplace in the 1970s and 80s, but it wasn’t until the 1990s that the productivity gains of all those PCs were finally felt.
What they’re saying: “Often times in the short term it can be costly to invest in new business processes and skills, and during that time you won’t see productivity rising,” Byrnjolfsson told me earlier this year.
• “But in the years after you’ll see the upwards part of the J, and COVID-19 has catalyzed the energy and creativity around this process.”
By the numbers: A survey by the World Economic Forum in October found more than 80% of global firms plan to accelerate the digitization of business process and grow remote work, while half plan to accelerate automation.
• About 43% expect those changes to reduce their workforces overall, which implies an expected increase in productivity.
The catch: If those gains don’t filter down to workers — or worse, end up eliminating jobs without replacing them with better ones — even a faster, more productive economy won’t ameliorate the inequality-driven political divisions that have dogged the U.S. in recent years.
The bottom line: As bad as 2020 has been, we may look back upon it as the year that finished the launchpad for a new Roaring ’20s.
Northwestern University Has Developed An AI System That Helps Detect Covid-19 On Chest X-Rays
This could potentially act as a rapid screening and triage tool.
— Read on www.forbes.com/sites/saibala/2020/11/29/northwestern-university-has-developed-an-ai-system-that-helps-detect-covid-19-on-chest-x-rays/
Earlier last week, Northwestern University researchers announced that they successfully created a new Artificial Intelligence (AI) radiology tool that can detect Covid-19 in chest x-rays.
The study has since been published in the journal Radiology, and indicates that the system “classified 2,214 test images with an accuracy of 83%.”
Dr. Aggelos Katsaggelos, a senior author of the study, states in the press report that “We are not aiming to replace actual testing […] X-rays are routine, safe and inexpensive. It would take seconds for our system to screen a patient and determine if that patient needs to be isolated.” Dr. Ramsey Wehbe, another main author of the study, explained that “It could take hours or days to receive results from a COVID-19 test […] A.I. doesn’t confirm whether or not someone has the virus. But if we can flag a patient with this algorithm, we could speed up triage before the test results come back.”
As Katsaggelos so aptly describes, the ability to conduct an initial screening to see if patients need to be isolated could itself be a potentially massive value addition to emergency department physicians. During the height of the pandemic, and still in many places, personal protective equipment (PPE) was one of the first supplies to run low, meaning that healthcare professionals were routinely seeing coronavirus positive patients without protection for themselves, potentially exacerbating the spread of the virus. In fact, this caused many healthcare workers to often reuse and stretch out limited supplies of PPE for patient care. Per the Centers for Disease Control and Prevention (CDC), so far, nearly 238,000 healthcare professionals have contracted Covid-19, with over 841 having passed away due to the virus.
The discussion in the journal article also provides an important consideration of this technology: “Prior clinical studies showed COVID-19 pneumonia produces characteristic features on chest imaging, but up to 56% of symptomatic patients can demonstrate normal chest imaging, especially early in their disease course. Imaging is therefore inappropriate to “rule out” disease. Also, many of the findings seen in COVID-19 imaging are non-specific with overlap, particularly with other viral pneumonias. Chest imaging therefore should not be used as a diagnostic tool for COVID-19, but could play an important role in earlier identification of patients likely to have the disease to aid in triage and infection control.”
The press report does also warn that “Of course, not all COVID-19 patients show any sign of illness, including on their chest X-rays. Especially early in the virus’ progression, patients likely will not yet have manifestations on their lungs.” In these cases, this AI radiology tool will likely not be very helpful.
Nonetheless, as the authors of the study so aptly conclude: “We feel that this algorithm has the potential to benefit healthcare systems in mitigating unnecessary exposure to the virus by serving as an automated tool to rapidly flag patients with suspicious chest imaging for isolation and further testing.” Indeed, if this screening tool continues to be further tested, and can be proven to be efficacious, safe, viable, and somewhat scalable, it may potentially be able to help alleviate some of the burden that healthcare workers face.
The content of this article is not implied to be and should not be relied on or substituted for professional medical advice, diagnosis, or treatment by any means, and is not written or intended as such. This content is for information and news purposes only. Consult with a trained medical professional for medical advice.
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Is Text-Based Therapy Effective?
What to know about the benefits and limitations of AI-operated chatbots
— Read on lifehacker.com/is-text-based-therapy-effective-1845593661
Oncology practice uses AI to significantly improve end-of-life care | Healthcare IT News
Northwest Medical Specialties’ palliative care consults nearly doubled. Hospice referrals increased twelvefold. The integration of palliative care with advanced cancer helped the practice reach quality benchmarks.
— Read on www.healthcareitnews.com/news/oncology-practice-uses-ai-significantly-improve-end-life-care