I am regularly asked to summarize my many posts. I thought it would be a good idea to publish on this blog, every Monday, some of the most relevant articles that I have already shared with you on my social networks.
Today I will share some of the most relevant articles about Artificial Intelligence and in what form you can find it in today’s life. I will also comment on the articles.
On makeuseof.com: https://www.makeuseof.com/ethical-dilemmas-in-artificial-intelligence/
The Top 4 Ethical Dilemmas in Artificial Intelligence. AI is everywhere, but how does it make decisions, balance society, and remain free from bias? These days, technology is making leaps in an unprecedented manner. In the palm of our hands, we can see and talk to someone from the other side of the world. We can order everything from a nice, warm meal, even to a car with just a few clicks. In the whole of human history, it’s never been so easy to connect and consume at the same time. At the heart of our modern conveniences are a mix and match of various types of emerging technology, including artificial intelligence. While it’s easy to think AI is all sunshine and roses, the reality is a little more complex than that. But, what is AI, and why should we be a little worried?
FDA Convenes Medical Device Workshop Focused on Artificial Intelligence and Machine Learning Transparency. On October 14, 2021, the U.S. Food and Drug Administration (“FDA” or the “Agency”) held a virtual workshop entitled, Transparency of Artificial Intelligence (“AI”)/Machine Learning (“ML”)-enabled Medical Devices. The workshop builds upon previous Agency efforts in the AI/ML space. The October 2021 workshop sought to expand upon FDA’s current Action Plan. The workshop’s objectives included exploring what transparency means to manufacturers, providers, and patients in relation to AI/ML-enabled medical devices; why such transparency matters; and how transparency can be achieved. Generally, the workshop emphasized the role transparency plays in creating safer, more effective AI/ML-enabled devices and in establishing trust in patients and providers using or prescribing such products. Below, we outline other key workshop themes.
On analyticsinsight.net: https://www.analyticsinsight.net/artificial-intelligence-has-found-ghost-ancestor/
Artificial intelligence has found an unknown ‘ghost’ ancestor in the human genome. Recently, researchers have uncovered evidence of a very different teenage girl who was over 50,000 years old and have strange uniqueness as looks like a ‘hybrid’ ancestor to modern humans that scientists had never seen before, and surprisingly she was not alone. In a study conducted in 2019, in order to analyze the complex mess of humanity’s prehistory, scientists used artificial intelligence (AI) to detect an unknown human ancestor species that modern humans encountered – and shared dalliances with – on the long trek out of Africa millennia ago. Around 80,000 years prior, the alleged out of Africa happened, when part of the human populace, which previously comprised of present-day people, deserted the African landmass and moved to different mainlands, bringing about every one of the current populaces.
On RAPS.org: https://www.raps.org/news-and-articles/news-articles/2021/10/regulators-release-10-principles-for-good-machine
Regulators release 10 principles for good machine learning practice. Regulators from the US, Canada, and the United Kingdom unveiled 10 principles to guide the development of good machine learning practice for medical devices.
The principles are meant to be used to drive the adoption of good practices that have been proven in other sectors, to help tailor those practices so that they are applicable to medical technology, and to create new practices specific to the health care sector. The document, which was issued by the US Food and Drug Administration (FDA), Health Canada, and the UK’s Medicines & Healthcare products Regulatory Agency (MHRA), is aimed at informing the work of the International Medical Devices Regulators Forum (IMDRF) and other international standards organizations as they tackle regulation of a growing number of medical devices that incorporate machine learning and artificial intelligence.
Making machine learning more useful to high-stakes decision makers. A visual analytics tool helps child welfare specialists understand machine learning predictions that can assist them in screening cases. The U.S. Centers for Disease Control and Prevention estimates that one in seven children in the United States experienced abuse or neglect in the past year. Child protective services agencies around the nation receive a high number of reports each year (about 4.4 million in 2019) of alleged neglect or abuse. With so many cases, some agencies are implementing machine learning models to help child welfare specialists screen cases and determine which to recommend for further investigation.
On Fortune.com: https://fortune.com/2021/10/27/ai-artificial-intelligence-business-strategy-data-accenture/
A.I. can be a cornerstone of success—but only if leaders make the right choices. First and foremost is the imperative to embrace these rapid technological advances that are driving the fourth industrial revolution. For any company that wants to position itself for growth, betting on this agenda is an insurance policy for long-term success. Big data and A.I. radically improve innovation, speed, and agility, which are the lifeblood of all effective organizations. Against this backdrop, it’s alarming that 76% of C-suite executives say they struggle with how to scale A.I., according to Accenture’s research, even though 84% believe it is critical to their business objectives. But perhaps we shouldn’t be so quick to judge. After all, 90% of the data in the world was created in the past two years, and forecasts suggest 175 zettabytes of data will be produced by 2025. It’s hardly surprising that collecting, storing, analyzing, and consuming such huge volumes of information remains out of reach for most organizations. But that urgently needs to change if they want to keep pace and differentiate in the new, technology-led global economy.
Discovering exoplanets using artificial intelligence. By implementing artificial intelligence techniques similar to those used in autonomous cars, a team from the UNIGE and the UniBE, in partnership with the company Disaitek, has discovered a new method for detecting exoplanets.