Comprehensive software reviews to make better IT decisions
Google Builds AI-Powered Tools for Patient Care: Project Nightingale
Google’s Q2 announcement that it helps “healthcare organizations like Ascension improve the healthcare experience and outcomes” recently got it in hot water. Google has been accused of secretly collecting sensitive patient data across 21 states in the US on behalf of Ascension, with neither doctors nor patients being informed. While most of the criticism has been about data privacy – which is undoubtedly tremendously important – we should also pause and consider what Google intends this data for.
Project Nightingale, as it is known, builds on Google’s previous investments and partnerships in the healthcare space, including a recent acquisition of Fitbit. The objective is clear: back in 2017, Google wrote of machine learning (ML) being “mature enough to start accurately predicting medical events – such as whether patients will be hospitalized, how long they will stay, and whether their health is deteriorating despite treatment for conditions such as urinary tract infections, pneumonia, or heart failure.”
Using data from Ascension and its patients, Google is building – and testing – applications that use ML to predict patient needs and hence increase the provider’s readiness. It’s a sort of “AI assistant for nurses and doctors.” In its blog, Google writes about “Extending tools to doctors and nurses to improve care: We aim to provide tools that Ascension could use to support improvements in clinical quality and patient safety.”
Apps like these should indeed increase treatment quality, improve patient outcomes, save lives, and enhance provider efficiencies. And more healthcare data, from hospital systems but also from wearable devices – both personal devices such as Fitbit and devices used by hospitals – will lead to better predictions. And better predictions will lead to better diagnostics and better treatments.
But there’s more. Better predictions and better outcomes strengthen the provider’s market position. After all, who wants treatment from a mediocre hospital, doctor, lab, etc.? And by “provider,” we mean not just the provider of healthcare services but also the vendor providing the technology – in this case, Google.
Market position is synonymous with power. And AI is a flywheel technology that has the potential to shift power within companies, within industries, and even globally between countries, writes Ajay Agrawal, author of “Prediction Machines” and co-chair of this year’s conference on Machine Learning and the Market for Intelligence at the University of Toronto’s Rotman School of Management.
In the medical domain, Agrawal says, AI could “consolidate and dramatically impact the structure and dynamics of the entire system.” And that’s the real goal of Google’s healthcare partnerships and acquisitions: to dominate healthcare, just like it dominates information access and advertisement markets.
Want to Know More?
If you are in the healthcare space, it’s not too late to start using AI. See our blueprint Get Started With AI to learn what others are doing with AI and explore what AI can do for you.
Recently I attended the inaugural Emotion AI conference, organized by Seth Grimes, a leading analyst and business consultant in the areas of natural language processing, text analytics, sentiment analysis, and their business applications. So, what is emotion AI, why is it relevant, and what do you need to know about it?
SortSpoke’s novel approach to machine learning answers a longstanding problem in financial services – how to efficiently extract critical data from inbound, unstructured documents at 100% data quality.
Amazon is offering its cashierless store technology to other retailers. The technology known as “Just Walk Out” eliminates checkout lines, offering an “effortless” shopping experience and shifting store associates to “more valuable activities”.
As the COVID-19 pandemic is shutting down whole countries, a few of you may be wondering whether AI can help create a vaccine for the virus responsible. After all, AI is magic, right?
Alphabet is facing backlash from its shareholders over its approach to digital privacy, reports the Financial Times. And not for the first time. This time, however, things will need to change.
The EU plans to invest €6 billion to build a single European data space, reports EURACTIV. The envisioned space will house personal, business, and “high-quality industrial data” and create the infrastructure for data sharing and use across businesses and nations.
“Facebook quietly acquired another UK AI startup and almost no one noticed,” reported TechCrunch on February 10. We looked into why.
In a landmark ruling, a Dutch court has ordered an immediate halt to the government’s use of an automated system for detection of welfare fraud.
Databricks, a data processing and analytics platform with a strong focus on AI and ML, has partnered with Immuta to deliver automated end-to-end data governance for AI, data science, and ML projects.