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Artificial intelligence and human rights

Artificial Intelligence raises important and urgent issues. AI is already with us changing the information that we receive, the choices that we make, and the ways in which our societies function. In the coming years AI will play an even greater role in the way that governments and public institutions operate, and the way in which citizens interact and participate in the democratic process.

It is clear that AI presents both benefits and risks. We need to ensure that AI promotes and protects our standards. I look forward to the outcome of the work of the Ad hoc Committee on Artificial Intelligence (CAHAI), mandated by the Committee of Ministers to examine the feasibility and potential elements on the basis of broad multi-stakeholder consultations, of a legal framework for the development, design and application of artificial intelligence, based on the Council of Europes standards on human rights, democracy and the rule of law. [Full statement]

Marija Pejinovi BuriSecretary General of the Council of Europe

Artificial intelligence (AI) will have an impact on our societies that we hardly imagine. Algorithms are already said to be able to identify the best candidates for a job, assist doctors to establish medical diagnoses or help lawyers before the courts. All this is not entirely new, since already in the 1980s, expert systems assisted humans with a high level of expertise. What is new today is that computers are increasingly able to perform extremely complex tasks independently, but their designers sometimes no longer understand how, what has happened in the "black box" of deep learning.

Therefore, we clearly need regulation to leave essential decision-making to humans and not to mathematical models, whose adequacy and biases are not controlled. [Full statement]

Jan KleijssenDirector, Information Society - Action against Crime

@JKleijssen

Continued here:
Council of Europe and Artificial Intelligence

The Verge is a place where you can consider the future. So are movies. In Yesterdays Future, we revisit a movie about the future and consider the things it tells us about today, tomorrow, and yesterday.

The movie: A.I. Artificial Intelligence

The future: A.I. begins with a brief summary of the sorry state of the world: climate change has melted the polar ice caps, wiping out coastal cities and severely reducing the human population. With regulations in place for reproduction on a resource-starved planet, corporations developed Mecha androids that appear human but lack emotions. Theyre seen as objects useful for labor or sex work, just human enough to not be strange but machine enough to not mistake them for people.

The story kicks into gear when Professor Allen Hobby (William Hurt) pitches taking Mecha to the next level: a machine that can love. That Mecha becomes David (Haley Joel Osment), an experimental Mecha designed to imprint on his owners and love them unconditionally, forever. And it works David is given to a grieving couple whose son is in suspended animation due to a rare disease. After some hijinks, hes accepted, until Martin, the boy hes filling in for, comes back.

Unfortunately Martin is cruel, and thanks to his manipulation, David is forced from home into a Pinocchio-esque journey to find a Blue Fairy and become a real boy. Through his eyes, we see a nihilistic theme-park vision of the future, where little is done to solve the still-looming climate apocalypse but neon cities and their pleasures boom.

The past: A.I. was released in 2001, but was originally going to come out long before that. Based on Brian Aldiss 1969 short story Supertoys Last All Summer Long, the film began as a Stanley Kubrick project in the 70s, languishing in development hell until the famed directors death in 1999. Steven Spielberg then took over, reportedly hewing closely to the plans Kubrick had for the film.

This meant that, at the time, the critical reception of A.I. largely revolved around its status as a strange hybrid of Kubrick and Spielbergs sensibilities, the last work of an idiosyncratic master carried out by one of his most prominent and stylistically different admirers. Most, like Roger Ebert, felt that the result was a frustrating film, attempting to parse where one mans vision ended and the others began.

But A.I. was an extremely fitting film for 2001, a year characterized by cinematic restlessness. Unsettling arthouse classics Donnie Darko and Mulholland Drive premiered. Shrek, which skewered Disney-style fairy tales with pop culture cynicism, also arrived, unwittingly laying the groundwork for surreal internet memes a decade later. Films that would spawn, extend, or hope to begin franchises floundered in every direction, with understated hits like Oceans Eleven arriving alongside strange blockbusters like Jurassic Park III and showstoppers like The Fellowship of the Ring.

No one knew what the 21st century would mean for movies, and a sad sci-fi fairytale about a robot boy created to stand in the void between a bleak future and an idyllic past could not have been a better match for the times.

The present: At first glance, the hedonistic carnival of A.I.s cities do not seem to hew terribly close to our current moment. Like a lot of cinematic futures, this one seems too loud, too garish, to ever be real. Jude Law as Gigolo Joe? The horrific robot bloodsport of the Flesh Fair, where obsolete robots battle to the death? We dont really have anything like that yet, right?

Only we do. The seeds of this future have already bloomed in our present. Its subtext is our subtext, a world formed by people with all the power afforded them by technology but none of the will to dream or love. The former would demand a clear-eyed response to shared crises looming ahead both at home and abroad; the latter would lead us to wield our innovations compassionately. Instead we have a world where algorithms reinforce biases and outrage is commodified, where every innovation is part and parcel with a new indignity. A lack of humanity that at every turn denies the option of a better future for all in favor of a more extravagant present for a few.

In A.I.s final 20 minutes, its revealed that this is the end of the world. In 2,000 more years, climate change will claim the last habitable portion of the Earth, and David will be the only one left who remembers humanity. Still a child, all David wants to remember is the human mother he imprinted on, but the viewer remembers everything else that the world was doomed by rage at the pending self-imposed disaster that humanity refused to face and instead directed toward the Mecha they created, the Mecha that would outlast them.

They made us too smart, too quick, and too many, Gigolo Joe, the Mecha sexbot that becomes Davids unlikely companion, says in one of his final scenes. In the end, all that will be left is us. Thats why they hate us

A.I. is refreshing because it is not interested in the question of whether or not we should create self-aware synthetic life, but instead asks what our responsibility toward it would be. If you can create a robot to love a human, one character asks early in the film, how do you get a human to love them back?

In the end it doesnt matter. Humanity doesnt even love itself enough to ensure its own survival.

Originally posted here:
A.I. Artificial Intelligence shows us a future where we neglect to dream - The Verge

An important aspect of treating patients with conditions like diabetes and heart disease is helping them stay healthy outside of the hospital before they to return to the doctors office with further complications.

But reaching the most vulnerable patients at the right time often has more to do with probabilities than clinical assessments. Artificial intelligence (AI) has the potential to help clinicians tackle these types of problems, by analyzing large datasets to identify the patients that would benefit most from preventative measures. However, leveraging AI has often required health care organizations to hire their own data scientists or settle for one-size-fits-all solutions that arent optimized for their patients.

Now the startup ClosedLoop.ai is helping health care organizations tap into the power of AI with a flexible analytics solution that lets hospitals quickly plug their data into machine learning models and get actionable results.

The platform is being used to help hospitals determine which patients are most likely to miss appointments, acquire infections like sepsis, benefit from periodic check ups, and more. Health insurers, in turn, are using ClosedLoop to make population-level predictions around things like patient readmissions and the onset or progression of chronic diseases.

We built a health care data science platform that can take in whatever data an organization has, quickly build models that are specific to [their patients], and deploy those models, says ClosedLoop co-founder and Chief Technology Officer Dave DeCaprio 94. Being able to take somebodys data the way it lives in their system and convert that into a model that can be readily used is still a problem that requires a lot of [health care] domain knowledge, and thats a lot of what we bring to the table.

In light of the Covid-19 pandemic, ClosedLoop has also created a model that helps organizations identify the most vulnerable people in their region and prepare for patient surges. The open source tool, called the C-19 Index, has been used to connect high-risk patients with local resources and helped health care systems create risk scores for tens of millions of people overall.

The index is just the latest way that ClosedLoop is accelerating the health care industrys adoption of AI to improve patient health, a goal DeCaprio has worked toward for the better part of his career.

Designing a strategy

After working as a software engineer for several private companies through the internet boom of the early 2000s, DeCaprio was looking to make a career change when he came across a project focused on genome annotation at the Broad Institute of MIT and Harvard.

The project was DeCaprios first professional exposure to the power of artificial intelligence. It blossomed into a six year stint at the Broad, after which he continued exploring the intersection of big data and health care.

After a year in health care, I realized it was going to be really hard to do anything else, DeCaprio says. Im not going to be able to get excited about selling ads on the internet or anything like that. Once you start dealing with human health, that other stuff just feels insignificant.

In the course of his work, DeCaprio began noticing problems with the ways machine learning and other statistical techniques were making their way into health care, notably in the fact that predictive models were being applied without regard for hospitals patient populations.

Someone would say, I know how to predict diabetes or I know how to predict readmissions, and theyd sell a model, DeCaprio says. I knew that wasnt going to work, because the reason readmissions happen in a low-income population of New York City is very different from the reason readmissions happen in a retirement community in Florida. The important thing wasnt to build one magic model but to build a system that can quickly take somebodys data and train a model thats specific for their problems.

With that approach in mind, DeCaprio joined forces with former co-worker and serial entrepreneur Andrew Eye, and started ClosedLoop in 2017. The startups first project involved creating models that predicted patient health outcomes for the Medical Home Network (MHN), a not-for-profit hospital collaboration focused on improving care for Medicaid recipients in Chicago.

As the founders created their modeling platform, they had to address many of the most common obstacles that have slowed health cares adoption of AI solutions.

Often the first problems startups run into is making their algorithms work with each health care systems data. Hospitals vary in the type of data they collect on patients and the way they store that information in their system. Hospitals even store the same types of data in vastly different ways.

DeCaprio credits his teams knowledge of the health care space with helping them craft a solution that allows customers to upload raw data sets into ClosedLoops platform and create things like patient risk scores with a few clicks.

Another limitation of AI in health care has been the difficulty of understanding how models get to results. With ClosedLoops models, users can see the biggest factors contributing to each prediction, giving them more confidence in each output.

Overall, to become ingrained in customers operations, the founders knew their analytics platform needed to give simple, actionable insights. That has translated into a system that generates lists, risk scores, and rankings that care managers can use when deciding which interventions are most urgent for which patients.

When someone walks into the hospital, its already too late [to avoid costly treatments] in many cases, DeCaprio says. Most of your best opportunities to lower the cost of care come by keeping them out of the hospital in the first place.

Customers like health insurers also use ClosedLoops platform to predict broader trends in disease risk, emergency room over-utilization, and fraud.

Stepping up for Covid-19

In March, ClosedLoop began exploring ways its platform could help hospitals prepare for and respond to Covid-19. The efforts culminated in a company hackathon over the weekend of March 16. By Monday, ClosedLoop had an open source model on GitHub that assigned Covid-19 risk scores to Medicare patients. By that Friday, it had been used to make predictions on more than 2 million patients.

Today, the model works with all patients, not just those on Medicare, and it has been used to assess the vulnerability of communities around the country. Care organizations have used the model to project patient surges and help individuals at the highest risk understand what they can do to prevent infection.

Some of it is just reaching out to people who are socially isolated to see if theres something they can do, DeCaprio says. Someone who is 85 years old and shut in may not know theres a community based organization that will deliver them groceries.

For DeCaprio, bringing the predictive power of AI to health care has been a rewarding, if humbling, experience.

The magnitude of the problems are so large that no matter what impact you have, you dont feel like youve moved the needle enough, he says. At the same time, every time an organization says, This is the primary tool our care managers have been using to figure out who to reach out to, it feels great.

See the rest here:
Bringing the predictive power of artificial intelligence to health care - MIT News