Tag: Generative

Generative AI Is Going To Shape The Mental Health Status Of Our Youths For Generations To Come

In today’s column, I am continuing my ongoing series about the impact of generative AI in the health and medical realm. The focus this time is once again on the mental health domain and involves the startling realization that generative AI is indubitably aiming to shape the mental health of our current and future generations. Kids and teens today and in subsequent generations will be using generative AI as a normal part of their everyday lives, including using ordinary generative AI to be their 24×7 always-on mental health therapist.

Let that soak in for a moment.

It is a sobering thought.

I have previously examined numerous interleaving facets of generative AI and mental health, see my comprehensive overview at the link here. You might also find of notable interest a CBS 60 Minutes episode that recently examined crucial facets of this evolving topic, see the link here (I was interviewed and appeared in the episode).

Other useful background includes my coverage of mental health chatbots that have been bolstered by generative AI (see the link here) and the rapidly changing nature of the client-therapist relationship due to generative AI at the link here. I explored where things are headed regarding the levels of AI-based mental therapy autonomous guidance at the link here, and showcased the importance of the World Health Organization (WHO) report on global health and generative AI at the link here, and so on.

Let’s unpack today’s focus.

Slowing And Inextricably Rolling Forward In Plain Sight

Here’s the deal about existing and upcoming generations of our youths.

With the advent of seemingly fluent generative AI that gained widespread attention via the launch of ChatGPT in November 2022, there are teens

WHO unveils a digital health promoter harnessing generative AI for public health

Ahead of World Health Day, focused on ‘My Health, My Right’, the World Health Organization (WHO) announces the launch of S.A.R.A.H., a digital health promoter prototype with enhanced empathetic response powered by generative artificial intelligence (AI).

S.A.R.A.H. is a Smart AI Resource Assistant for Health that represents an evolution of AI-powered health information avatars, using new language models and cutting-edge technology. It can engage users 24 hours a day in 8 languages on multiple health topics, on any device.

WHO’s digital health promoter is trained to provide information across major health topics, including healthy habits and mental health, to help people optimize their health and well-being journey. It aims to provide an additional tool for people to realize their rights to health, wherever they are.

S.A.R.A.H., also known as Sarah, has the ability to support people in developing better understanding of risk factors for some of the leading causes of death in the world, including cancer, heart disease, lung disease, and diabetes. She can help people access up-to-date information on quitting tobacco, being active, eating a healthy diet, and de-stressing among other things. 

“The future of health is digital, and supporting countries to harness the power of digital technologies for health is a priority for WHO,” said WHO Director-General Dr Tedros Adhanom Ghebreyesus. “S.A.R.A.H. gives us a glimpse of how artificial intelligence could be used in future to improve access to health information in a more interactive way. I call on the research community to help us continue to explore how this technology could narrow inequities and help people access up-to-date, reliable health information.” 

S.A.R.A.H. is now powered by generative AI rather than a pre-set algorithm or script helping her to provide more accurate responses in real-time; engage in dynamic personalized conversations at scale that more accurately mirror human interactions

Exploring The Vexing Question Of Whether Generative AI Can Perform Mental Health Reasoning Or Maybe The Psychological Advice Generated Is Just Mindless Mimicry

In today’s column, I am continuing my ongoing series about the impact of generative AI in the health and medical realm. The focus this time is on the use of generative AI to aid in performing mental health therapy, which I’ve previously covered extensively from a variety of perspectives such as the client-therapist relationship transformations at the link here and where things are headed concerning the levels of AI-based mental therapy autonomous guidance at the link here, just to name a few.

The particular interest here is whether generative AI can perform mental health reasoning.

Allow me to emphasize that the catchphrase of “mental health reasoning” is the place where we all enter into a complex murky space and ought to be extremely mindful of what the expression signifies and what if anything it has to do with AI, including and especially generative AI.

I shall first set the stage for this elucidation and lay out the course of the journey herein.

Words About Thoughts Are Very Important

Suppose that a person opts to use generative AI for advice on a mental health concern. The person engages in a back-and-forth dialogue with the generative AI, such as an illustrative discourse that I closely analyzed in detail regarding experiencing ADHD (attention deficit hyperactivity disorder), see my analysis at the link here. There isn’t a human therapist in the loop. In other words, this is someone who has sought out the use of generative AI on their own and is not under the care of a human therapist.

In case you think the above scenario is an outlier or rarity, please be aware that the use of generative AI for mental health guidance is readily available right now. There are

Do We Want Generative AI That Backs Down When Giving Personalized Mental Health Advice Or Lean Instead Into Brazen Boldness?

In today’s column, I continue to extend my ongoing deep dive analyses about generative AI that is or can be anticipated to be used for mental health guidance or advisement. The focus of this discussion is concerning the potential for generative AI to be wishy-washy when dispensing personalized mental health advice to humans. The question arises as to whether AI that seemingly waffles or appears non-committal when actively proffering advice is desirable or undesirable as a devised mental health therapeutic approach.

Before I get into that particular topic, I’d like to provide a quick background for you so that you’ll have a suitable context about the arising use of generative AI for mental health advisement purposes. I’ve mentioned this in prior columns and believe the contextual establishment is essential overall.

The use of generative AI for mental health treatment is a burgeoning area of tremendously significant societal ramifications. We are witnessing the adoption of generative AI for providing mental health advice on a widescale basis, yet little is known about whether this is beneficial to humankind or perhaps contrastingly destructively adverse for humanity.

Some would affirmatively assert that we are democratizing mental health treatment via the impending rush of low-cost always-available AI-based mental health apps. Others sharply decry that we are subjecting ourselves to a global wanton experiment in which we are the guinea pigs. Will these generative AI mental health apps steer people in ways that harm their mental health? Will people delude themselves into believing they are getting sound mental health advice, ergo foregoing treatment by human mental therapists, and become egregiously dependent on AI that has no demonstrative mental health improvement outcomes?

Hard

Google Cloud Launches New Generative AI Capabilities for Healthcare

Google Cloud has been on a relentless spree with its generative AI capabilities. Over the past year, the company has dedicated significant resources to building out its robust suite of tools, including its well-known Vertex AI Search platform, which enables organizations to easily build generative AI powered search tools.

Its latest innovation in this space is its introduction of new capabilities in Vertex AI specifically tailored for healthcare and life-sciences organizations, which the company announced today. Specifically, the new features will harness Vertex AI’s existing capabilities to search across data sources to go one step further and help organizations search for clinical information and study patient records more easily.

The value of these new capabilities is incredible. Most importantly, making search functions available at a granular enough level to encompass data across an entire organization’s ecosystem, in addition to data within EHRs (electronic health records), can significantly improve clinical workflows and the process of care delivery. For example, a clinician may be able to use a tool utilizing this technology to search a patient’s records to easily find the patient’s medication history, previous labs, and other information related to the patient’s care plan.

Furthermore, Google Cloud’s technology prides itself on two unique aspects. First, the product is designed to be incredibly intuitive and easy to use, meaning that organizations can deploy custom machine learning models with minimal expertise and experience. Moreover, the product boasts its interoperability features, enabling organizations to search across a wide spectrum of data sources, ranging from clinical notes to raw, unstructured data in the patient record. Given how siloed medical data is currently, this is a significant boon to healthcare organizations.

care.AI, an AI-powered ambient intelligence company, announced today that it will be integrating Google

Google’s new generative AI lets you preview clothes on different models

Google, ever eager to lean into generative AI, is launching a new shopping feature that shows clothes on a lineup of real-life fashion models.

A part of a wide range of updates to Google Shopping rolling out in the coming weeks, Google’s virtual try-on tool for apparel takes an image of clothing and attempts to predict how it would drape, fold, cling, stretch and form wrinkles and shadows on a set of real models in different poses.

Virtual try-on is powered by a new diffusion-based model Google developed internally. Diffusion models — which include the text-to-art generators Stable Diffusion and DALL-E 2 — learn to gradually subtract noise from a starting image made entirely of noise, moving it closer, step by step, to a target.

Google trained the model using many pairs of images, each including a person wearing a garment in two unique poses — for instance, an image of someone wearing a shirt standing sideways and another of them standing forward. To make the model more robust (i.e., combat visual defects like folds that look misshapen and unnatural), the process was repeated using random image pairs of garments and people.

Google try-on

Google’s new AI-powered try-on feature, which taps generative AI to adapt clothing to different models.

Starting today, U.S. shoppers using Google Shopping can virtually try on women’s tops from brands including Anthropologie, Everlane, H&M and LOFT. Look for the new “Try On” badge on Google Search. Men’s tops will launch later in the year.

“When you try on clothes in a store, you can immediately tell if they’re right for you,” Lilian Rincon, senior director of consumer shopping product at Google, wrote in a blog post shared with TechCrunch. She cites a survey showing that 42% of online shoppers don’t feel represented by images of models while 59%

Generative AI in style | McKinsey

As this season’s vogue weeks wrap up in London, Milan, New York, and Paris, models are doing work to create and market the styles they’ve just showcased on runways—and they are starting off up coming season’s collections. In the potential, it is entirely attainable that all those models will blend the prowess of a artistic director with the electricity of generative artificial intelligence (AI), helping to carry apparel and equipment to marketplace more rapidly, marketing them much more competently, and improving the purchaser experience.

By now, you’ve likely listened to of OpenAI’s ChatGPT, the AI chatbot that turned an right away feeling and sparked a digital race to establish and launch competition. ChatGPT is only a person consumer-friendly instance of generative AI, a technology comprising algorithms that can be used to develop new material, together with audio, code, photos, textual content, simulations, and video clips. Rather than basically identifying and classifying information and facts, generative AI produces new details by leveraging basis products, which are deep mastering products that can handle multiple complicated responsibilities at the identical time. Illustrations include GPT-3.5 and DALL-E. (For extra on generative AI and machine understanding, see “What is generative AI?”  and “Generative AI is here: How applications like ChatGPT could improve your company.”)

While the style business has experimented with essential AI and other frontier technologies—the metaverse, nonfungible tokens (NFTs), electronic IDs, and augmented or virtual reality come to mind—it has so far experienced small knowledge with generative AI. Correct, this nascent technological know-how became broadly out there only a short while ago and is continue to rife with worrisome kinks and bugs, but all indications are that it could enhance at lightning pace and come to be a activity changer in a lot of elements of company. In the next three to 5

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