Category Archives: Artificial Intelligence

Artificial intelligence was once just a buzzword, but today its impact on our daily lives is far greater than ever before.

Let us imagine that you have decided to find an online casino available in your area with great bonuses. You type a query into Google and discover Tonybet. Why were we given this answer? Because the intelligence of the system is artificial intelligence, which makes decisions to improve your user experience based on your preferences and your online behavior.

Artificial Intelligence has a huge impact on many other industries as well.

In medicine, search, languages, automobiles, and, of course, advertising, artificial intelligence has driven innovation. Heres how we assess the impact of artificial intelligence on our daily lives.

In this sphere, AI memory is valued, as well as the ability to generate and compare vast amounts of information.

For several years now, everyone has heard about IBM Watson and DeepMind Health (a Google development) smart assistants that not only give advice to doctors but also figure out the genetic predisposition to pathologies. For example, IBM Watson already identifies and develops therapy plans for 13 types of malignant neoplasms: from cervical cancer to colon cancer.

Artificial intelligence even comes to the aid of patients. Telemedicine applications that collect data from fitness bracelets and other sensors, as well as questionnaires that establish the exact symptoms and diseases of patients, are becoming increasingly popular. For example, AI can recognize tuberculosis and disorders of internal organs, including the brain.

Some of the apps parse human speech and respond verbally, while others prefer written communication. The apps get the necessary information and then make recommendations on what to do next, or send the data to a therapist. The most popular intelligent assistants are Yours.MD and Ada, which can be downloaded from the App Store or Google Play.

Of particular importance are systems that can develop new medicines. According to Pfizers top manager, it takes an average of 12 years to develop and bring a new medicine to market. AI will make it possible to create the molecular structure and simulate the drug, which will increase its quality and reduce the time it takes to produce new drugs. Atomwise and Berg Health are pioneering supercomputers that solve this problem.

Large industrial companies in countries such as Japan, China, the US, Germany, and Switzerland are investing in new technologies. The trend today is toward fewer jobs involving intellectual labor and more computers.

Such jobs will suffer in the coming decades:

Robotization soon will also affect such professions as secretaries, cashiers, truck drivers, and waiters. An example of successful AI implementation was the H&H line plant. The technology, which tracks the gaze of workers, helped save 400 hours of training for trainees in 1 year and reduce the likelihood of accidents.

MIT Technology Review reported that Andrew Eun, a robotics and machine learning researcher, is developing a new project called Landing.AI. It aims to set up a manufacturing mechanism in factories and plants. His first partner is Foxconn, which manufactures Apple gadgets.

Soon, the field of education will be developing rapidly in two directions adaptive learning and proctoring.

Adaptive learning is designed to solve the problem of different performances of pupils and students. The fact is that one person learns material much faster and more successfully than another. Therefore, AI will monitor the level of knowledge of the student and adapt the order of blocks of courses to his abilities or inform the teacher how well the student has mastered the material. An example of such a system could be the Third Space Learning platform, which is currently under development.

Proctoring represents the control of pupils and students during the passing of control and examination tests. Whereas in the past, students were in the crosshairs of a webcam, now AI comes to the rescue. It monitors how often a student takes his or her eyes off the computer screen, whether he or she changes tabs on a browser, and whether there are no extra voices in the room. As soon as the AI notices an irregularity, it immediately alerts the human lecturer.

But can the machine replace an ordinary teacher? Rosa Lukin, a professor at University College London, denies it. It is worth finding a compromise, she says. After all, the goal is not to replace teachers with machines, but to improve education. The human teacher is certainly indispensable here.

The opinion that farming and livestock are backward and old-fashioned industries is a thing of the past. Today, the intensive growth of the global AI market in the agricultural industry is caused by the following factors: introduction of the data management system, automation of irrigation, increase in productivity of crops through the introduction of learning methods and increase in the number of people on the planet. At the same time, the growth of the AI market is limited by the high cost of collecting information about agricultural lands.

The widespread introduction of robotics in agriculture is represented by such developments:

Energias Market Research predicts that the AI market in the agricultural industry will grow by 24.3% by 2024. It will actively develop in the U.S. and the Asia-Pacific region. Agworld, Farmlogs, Cropx, Microsoft, AGCO, and others are among the central players in the smart agribusiness market.

The goal of implementing AI in this area is to fight traffic jams. Such systems are already working successfully in major cities in Europe, North America, and Asia.

Collecting information from traffic lights, analysis of traffic density, traffic accidents, weather data, and other factors that create traffic jams these are the functions of the computer. As a result, the intelligent system monitors the roads online, predicts what the traffic will be, and according to this, switches the traffic lights.

It monitors not only the traffic on the road, but also helps the drivers. For example, if necessary, the system calls for a tow truck. This solution will not be able to get rid of traffic jams completely, but it is quite possible to speed up the traffic by several times.

Probably, progress will be notified if we see widespread use of unmanned cars, which are vehicles that can move without human intervention. They are being developed by Google, AKTIV, Tesla Motors, and some others.

Of course, everyone has heard of the smart house, which in the future will be a typical example of AI. The largest manufacturers are Yamaha, Siemens, Abb, Beckhoff, and Legrand.

Such developments simplify human life to the maximum. For example, such a system will open the curtains in the morning, wake up the owners and make coffee. In the future, the functionality of the smart house will be expanded up to the fact that the closet will automatically steam clothes and the refrigerator will order food. Such a solution will optimize costs related to power, ventilation, heating, adjusting to a convenient schedule.

Vacuum cleaners that can not only do the cleaning but also move objects and charge themselves remain popular as well.

Another example of a domestic AI application is automated translators. While in the past machine translation left much to be desired, today the situation has changed dramatically. Google Translate demonstrates this: the algorithm is based on the fact that the computer perceives not individual words, but a complete sentence. It allows to obtain high-quality text, so soon, this method will become the basis for automatic translation.

Human-like androids are used not only for household chores but also for communication. Iron friend will not let you die of boredom, and sometimes it becomes a full member of the family. So, one lucky man in China managed to marry a robot. He turned out to be engineer Zheng Jiajia, who made his own bride.

Undoubtedly, the future of humanity is intertwined with robots, because every year more and more applications of artificial intelligence are developed. Most likely, it will surpass the abilities of humans, but at the same time greatly improve the quality of their lives. The main thing here is to find reasonable limits before AI learns to reproduce itself. According to Elon Musk, it is worth taking a proactive stance and already now limiting the use of AI, at least in the military industry.

Read the rest here:

The Future Is Already Here: Areas Where Artificial Intelligence Is Already in Use and This Is Just the Beginning - Analytics Insight

Events over the past few years have revealed several human rights violations associated with increasing advances in artificial intelligence (AI).

Algorithms created to regulate speech online have censored speech ranging from religious content to sexual diversity. AI systems created to monitor illegal activities have been used to track and target human rights defenders. And algorithms have discriminated against Black people when they have been used to detect cancers or assess the flight risk of people accused of crimes. The list goes on.

As researchers studying the intersection between AI and social justice, weve been examining solutions developed to tackle AIs inequities. Our conclusion is that they leave much to be desired.

Some companies voluntarily adopt ethical frameworks that are difficult to implement and have little concrete effect. The reason is twofold. First, ethics are founded on values, not rights, and ethical values tend to differ across the spectrum. Second, these frameworks cannot be enforced, making it difficult for people to hold corporations accountable for any violations.

Even frameworks that are mandatory like Canadas Algorithmic Impact Assessment Tool act merely as guidelines supporting best practices. Ultimately, self-regulatory approaches do little more than delay the development and implementation of laws to regulate AIs uses.

And as illustrated with the European Unions recently proposed AI regulation, even attempts towards developing such laws have drawbacks. This bill assesses the scope of risk associated with various uses of AI and then subjects these technologies to obligations proportional to their proposed threats.

As non-profit digital rights organization Access Now has pointed out, however, this approach doesnt go far enough in protecting human rights. It permits companies to adopt AI technologies so long as their operational risks are low.

Just because operational risks are minimal doesnt mean that human rights risks are non-existent. At its core, this approach is anchored in inequality. It stems from an attitude that conceives of fundamental freedoms as negotiable.

So the question remains: why is it that such human rights violations are permitted by law? Although many countries possess charters that protect citizens individual liberties, those rights are protected against governmental intrusions alone. Companies developing AI systems arent obliged to respect our fundamental freedoms. This fact remains despite technologys growing presence in ways that have fundamentally changed the nature and quality of our rights.

Our current reality deprives us from exercising our agency to vindicate the rights infringed through our use of AI systems. As such, the access to justice dimension that human rights law serves becomes neutralised: A violation doesnt necessarily lead to reparations for the victims nor an assurance against future violations, unless mandated by law.

But even laws that are anchored in human rights often lead to similar results. Consider the European Unions General Data Protection Regulation, which allows users to control their personal data and obliges companies to respect those rights. Although an important step towards more acute data protection in cyberspace, this law hasnt had its desired effect. The reason is twofold.

First, the solutions favoured dont always permit users to concretely mobilize their human rights. Second, they dont empower users with an understanding of the value of safeguarding their personal information. Privacy rights are about much more than just having something to hide.

These approaches all attempt to mediate between both the subjective interests of citizens and those of industry. They try to protect human rights while ensuring that the laws adopted dont impede technological progress. But this balancing act often results in merely illusory protection, without offering concrete safeguards to citizens fundamental freedoms.

To achieve this, the solutions adopted must be adapted to the needs and interests of individuals, rather than assumptions of what those parameters might be. Any solution must also include citizen participation.

Legislative approaches seek only to regulate technologys negative side effects rather than address their ideological and societal biases. But addressing human rights violations triggered by technology after the fact isnt enough. Technological solutions must primarily be based on principles of social justice and human dignity rather than technological risks. They must be developed with an eye to human rights in order to ensure adequate protection.

One approach gaining traction is known as Human Rights By Design. Here, companies do not permit abuse or exploitation as part of their business model. Rather, they commit to designing tools, technologies, and services to respect human rights by default.

This approach aims to encourage AI developers to categorically consider human rights at every stage of development. It ensures that algorithms deployed in society will remedy rather than exacerbate societal inequalities. It takes the steps necessary to allow us to shape AI, and not the other way around.

View original post here:

We need concrete protections from artificial intelligence threatening human rights - The Conversation CA

As part of a series of longitudinal studies on AI, the Stanford HAI has come out with the new AI100 report titled Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. The report evaluates AIs most significant concerns in the previous five years.

Much has been written on the state of artificial intelligence and its effects on society since the initial AI100 report. Despite this, AI100 is unusual in that it combines two crucial features.

First, it is authored by a study panel of key multidisciplinary scholars in the fieldexperts who have been creating artificial intelligence algorithms or studying their impact on society as their primary professional activity for many years. The authors are experts in the field of artificial intelligence and offer an insiders perspective. Second, it is a long-term study, with periodic reports from study panels anticipated every five years for at least a century.

As AI systems demonstrate greater utility in real-world applications, they have expanded their reach, raising the likelihood of misuse, overuse, and explicit abuse. As the capabilities of AI systems improve and they become more interwoven into society infrastructure, the consequences of losing meaningful control over them grow more alarming.

New research efforts aim to rethink the fields foundations to reduce the reliance of AI systems on explicit and often misspecified aims. A particularly evident concern is that AI might make it easier to develop computers capable of spying on humans and potentially killing them on a large scale.

However, there are numerous more significant and subtler concerns at the moment.

One can access the entire report here.

Nivash has a doctorate in Information Technology. He has worked as a Research Associate at a University and as a Development Engineer in the IT Industry. He is passionate about data science and machine learning.

The rest is here:

Dangers Of Artificial Intelligence: Insights from the AI100 2021 Study - Analytics India Magazine

Bosses at NHS Golden Jubilee Hospital in Clydebank, West Dunbartonshire, said patients there who need stents fitted in their heart arteries are the first in Scotland to have the procedure performed using guided AI technology.

During percutaneous coronary intervention (PCI) operations to treat coronary artery disease, stents are placed in narrowed coronary arteries to keep them open and maintain blood flow to the heart.

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Cardiologists at the hospital carry out planned PCIs using the new Ultreon 1.0 Software which merges the existing imaging technique of Optical Coherence Tomography (OCT) which gives a view inside an artery with AI for better visualisation, enabling faster, more accurate decisions.

Using both tools together gives cardiologists a comprehensive view inside patients heart arteries, helping them to determine the best treatment for arterial calcification.

The software speeds up the operation, using infrared lasers and AI to measure how much of the artery is diseased and the size of stent required.

This helps ensure stents are more accurately fitted, leading to improved long term health for patients.

Consultant Interventional Cardiologist Dr Stuart Watkins said: As people get older they can develop hardening of the heart arteries due to calcification.

This makes treating the arteries difficult for cardiologists because calcium is very hard and it can limit the expansion of our stents.

Its very important to identify calcification in the heart arteries, which isnt always apparent from doing a basic coronary angiogram.

OCT gives us extremely detailed pictures within the arteries so that we can pick up calcification and determine the best treatment strategy before we put stents in.

Ultreon helps us quickly measure how much of the artery is diseased and what size of stent you have to put in, without taking too much time to do it.

One of the first patients treated with the new technology at the hospital was 85-year-old Chris Stevenson, originally from Duntocher, West Dunbartonshire, but now living in Larkhall, South Lanarkshire.

After suffering from heart problems from age 50, his condition worsened recently and he needed four stents fitted.

The retired mechanical engineer was awake for the three-hour procedure and hopes it will help him be more active.

He said: Ive been taking things quite slowly at the moment. My wife Betty wont even let me do my normal chores, but I feel fantastic.

Ive also had two knee replacements so I havent been able to do the hillwalking I love, but I would like to get back to just being able to go out and keep active, so hopefully this latest treatment will help me do that.

I know how hard the specialists worked for me, as well as all the staff who booked me in and cared for me on the ward. I cant praise them highly enough, they were amazing.

The hospitals medical director Dr Mark MacGregor said the technology is now on offer to patients across Scotland and provides the potential for significantly improved long-term outcomes.

He added: This new technology is an excellent advancement in treating coronary heart disease.

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Artificial Intelligence now used in life-saving operations for heart patients in Scotland - The Scotsman

Financial risk control and management is one of the most definitive early applications of AI in fintech. Image: Shutterstock

The AI apocalypse is here. Across industries, segments, walks of lifeone may not realise it but it is playing out large. Larger still is the opaque jargon and the hype around it. Not without basis though.

The race to reach the top has many participantsresearch institutes, top corporates, educational institutions, and even states around the world. Artificial intelligence-powered fintech startups are registering exponential growth and so is the venture capital funding for them. Adapting quickly to embrace digital and become an active part of the ecosystem is essential. Network-enabled co-creation is at the heart of the new digital transformation.

AI and fintechAI promises to completely transform everythingsome things more than others. The BFSI space has already seen the sheer efficiency of AI to process massive data logs and deliver masterful insights through pattern recognition. AI has made a huge difference in the world of payments and financial services which is plagued with incidences of identity fraud and imposter scams.

With the need to deliver better experiences and customer conveniences, AI enables better and faster fraud detection in a hyper-digitised world where PII (Personally Identifiable Information) is available for a few hundred dollars on the dark web. Advanced risk monitoring and fraud detection enables prediction and detection in real-time and not post factum.

From barter to paper currency to plastic money to contactless cards, the world of payments has come a long way. AI promises to usher in a new world of frictionless and seamless payments where the ubiquitous modern POS of today will look archaic. Amazons experiments to do away with the retail checkout queue are a good example.

AI and investingAI-powered robo-advisors are the 'in' thing what with their ability to go beyond mere algorithm power to considering far more complex parameters including a range of factors from tax-loss harvesting to financial planning.

The applications of AI include predicting consumer behaviour and enabling effective buying of hyper-relevant and personalised products, to offer tremendous opportunities to marketers of financial services.

Digitisation and decentralisation are at the core of powering the fintech revolution, enabled by AI. Besides AI, there is blockchain, robotic process automation, and data analytics which constitute other prominent technologies impacting fintech.

The structuring, delivery, and consumption of financial services have all been disrupted, courtesy AI, while the new technologies lend an umbrella branding to the fintech transformation. To capitalise on the opportunities being unleashed, it is imperative develop an enterprise-wide strategy and apply AI to revenue and customer engagement opportunities.

Financial risk control and management are the most definitive early applications of AI in fintech. It is helping restore trust in the financial systems and bringing inclusion with digital finance, bridging the gap between the hitherto unbanked and the banked. The pandemic has further hastened the pace at which AI adoption in fintech is becoming the norm.

The fintech market storyMordor intelligence predicts the AI fintech market at a projected $22-plus billion, growing at a CAGR of 23 percent by the year 2025. The top finance leaders around the world acknowledge the role of technologies led by blockchain and AI. The global fintech market has a predominant penetration in the APAC and Americas with the APAC market forecasted to be the fastest-growing region.

The frontrunners amongst Indian fintech companies using AI include Razorpay (AI-powered system Third Watch helps address fraud issues); INDmoney (AI-driven financial advisory); CogNext (regulatory tech company using AI through automated tech platform, Platform X); Capital Float; Credit Mate; Lending Kart, and Mswipe.

Industrial revolution 4.0 will see a fusion of technologies across physical, digital and biological spaces, and will allow reinventing the firm around data, connectivity, analytics and AI, which removes traditional limitations of scale, scope and learning.

The writer is an executive-in-residence at the Anderson School of Management, UCLA besides being a global CEO coach and C-Suite Advisor.

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How AI Is Transforming The World Of Finance - Forbes India

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The globalIoT in Agriculture Marketsize is expected to reach USD 30.8 billion by 2028, registering a CAGR of 10.6% over the forecast period, according to the latest report by Reports and Data.Major factors driving market revenue growth are the growing demand for agricultural output, increasing penetration of Internet of Things (IoT) & Artificial Intelligence (AI) technologies in the farming sector, and increasing government support for adoption of latest agricultural technologies along with growing focus on livestock monitoring to enhance efficiency in farming.

Internet of Things plays a critical role in increasing agricultural productivity. IoT technologies can solve agricultural problems and maximise the quantity and quality of agricultural production by linking farms via a shared network and providing them with information sharing, storage, and review options. In agriculture, the Internet of Things (IoT) is combined with advanced technological tools, equipment, and solutions to increase operational performance and minimise energy waste. In IoT-based smart farming, a system is designed to monitor crop field and automate irrigation system using sensors such as light, temperature, and humidity.

Some of the prominent companies in the market include Deere & Company, Trimble, Raven Industries, AGCO Corporation (AGCO), AgJunction Inc. (AgJunction), DeLaval, GEA Farm Technology, Lely, Antelliq, AG Leader Technology (AG Leader), Tigercat, Ponsse, Komatsu Forest AB, Caterpillar, Treemetrics, Topcon Positioning Systems, and DICKEY-john Corporation.

Fill the Sample Form to Get a FREE PDF Sample Copy of IoT in Agriculture Market Report-

Market Overview:

Information and communication technology (ICT) encompass a wide range of communication networks as well as the technologies that support them. The information and communication technology (ICT) sector bring together manufacturing and service businesses whose products primarily perform or enable information processing and communication via electronic methods, including transmission and display. The ICT sector contributes to technical advancement, increased output, and increased productivity. Its impact can be measured in a variety of ways: directly, as a contributor to output, employment, or productivity growth; or indirectly, as a source of technical development influencing other sections of the economy.

The IoT in Agriculture market has been segmented into key regions of the world and offers an analysis of growth rate, market share, market size, current and emerging trends, production and consumption ratio, industrial chain analysis, demand and supply, import and export, revenue contribution, and presence of key players in each region. A country-wise analysis of the market is offered in the report to gain a better understanding of the regional spread and progress of the IoT in Agriculture market.

The study throws light on the IoT in Agriculture market mainly focusing on the growth factors and even the restraining factors. The restraining factors are also provided with the best solutions which also prove to be a counteract to the drawback and help increase the market demand. Applications, types, technology and many other segmentations are studied to give a depth of knowledge for further market investment. Key driving forces for IoT in Agriculture market is explained to help give an idea for a detailed analysis of this market.

The report also implements primary and secondary research techniques for gathering the most crucial pieces of professional information, and applies a number of industry-best techniques upon the data for projecting the future state of the global IoT in Agriculture market. Based on current market development, the report includes an analysis of how activities such as mergers and shapes the markets future.

Conclusively, all aspects of the IoT in Agriculture market are quantitatively as well qualitatively assessed to study the global as well as regional market comparatively. This market study presents critical information and factual data about the market providing an overall statistical study of this market on the basis of market drivers, limitations and its future prospects.

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Rising Penetration of Internet of Things (IoT) & Artificial Intelligence (AI) technologies in the farmi... - TechBullion

Events over the past few years have revealed severalhuman rights violationsassociated with increasingadvances in artificial intelligence (AI).

Algorithms created to regulate speech onlinehave censored speechranging from religious content tosexual diversity. AI systems created to monitor illegal activities have been used totrack and target human rights defenders. And algorithms have discriminated against Black people when they have been used todetect cancersorassess the flight risk of people accused of crimes. The list goes on.

As researchers studying the intersection between AI and social justice, weve been examining solutions developed to tackle AIs inequities. Our conclusion is that they leave much to be desired.

Some companies voluntarily adoptethical frameworksthat are difficult to implement and have little concrete effect. The reason is twofold. First, ethics are founded on values, not rights, and ethical values tend todiffer across the spectrum. Second, these frameworks cannot be enforced, making it difficult for people to hold corporations accountable for any violations.

Even frameworks that are mandatory like CanadasAlgorithmic Impact Assessment Tool act merely as guidelines supporting best practices. Ultimately, self-regulatory approaches do little more thandelay the development and implementation of laws to regulate AIs uses.

And as illustrated with the European Unions recently proposedAI regulation, even attempts towards developing such laws have drawbacks. This bill assesses the scope of risk associated with various uses of AI and then subjects these technologies to obligations proportional to their proposed threats.

As non-profit digital rights organization Access Now has pointed out, however,this approach doesnt go far enough in protecting human rights. It permits companies to adopt AI technologies so long as their operational risks are low.

Just because operational risks are minimal doesnt mean that human rights risks are non-existent. At its core, this approach is anchored in inequality. It stems from an attitude that conceives of fundamental freedoms as negotiable.

So the question remains: why is it that such human rights violations are permitted by law? Although many countries possess charters that protect citizens individual liberties,those rights are protected against governmental intrusions alone. Companies developing AI systems arent obliged to respect our fundamental freedoms. This fact remains despite technologys growing presence in ways that have fundamentally changed the nature and quality of our rights.

Our current reality deprives us from exercising our agency to vindicate the rights infringed through our use of AI systems. As such, the access to justice dimension that human rights law serves becomes neutralised: A violation doesnt necessarily lead to reparations for the victims nor an assurance against future violations, unless mandated by law.

But even laws that are anchored in human rights often lead to similar results. Consider theEuropean Unions General Data Protection Regulation, which allows users to control their personal data and obliges companies to respect those rights. Although an important step towards more acute data protection in cyberspace, this law hasnt had its desired effect. The reason is twofold.

First,the solutions favoureddont always permit users to concretely mobilize their human rights. Second, they dont empower users withan understanding of the value of safeguarding their personal information.Privacy rights are about much more than just having something to hide.

These approaches all attempt to mediate between both the subjective interests of citizens and those of industry. They try to protect human rights while ensuring that the laws adopted dont impede technological progress. But this balancing act often results in merely illusory protection, without offering concrete safeguards to citizens fundamental freedoms.

To achieve this, the solutions adopted must be adapted to the needs and interests of individuals, rather than assumptions of what those parameters might be. Any solution must also includecitizen participation.

Legislative approaches seek only to regulate technologys negative side effects rather than address their ideological and societal biases. But addressing human rights violations triggered by technology after the fact isnt enough. Technological solutions must primarily be based on principles ofsocial justice and human dignity rather than technological risks. They must be developed with an eye to human rights in order to ensure adequate protection.

One approach gaining traction is known as Human Rights By Design. Here, companies do not permit abuse or exploitation as part of their business model. Rather, they commit to designing tools, technologies, and services to respect human rights by default.

This approach aims to encourage AI developers to categorically consider human rights at every stage of development. It ensures that algorithms deployed in society will remedy rather than exacerbate societal inequalities. It takes the steps necessary to allow us to shape AI, and not the other way around.

See the original post:

We need concrete protections from artificial intelligence threatening human rights Stuff - Stuff Magazines

ATLANTA, Sept. 26, 2021 /PRNewswire/ --At the 2021 AACC Annual Scientific Meeting & Clinical Lab Expo, laboratory medicine experts will present the cutting-edge research and technology that is revolutionizing clinical testing and patient care. From September 26-30 in Atlanta, Georgia, the meeting's 200-plus sessions will deliver insights on a broad range of timely healthcare topics. Highlights of these include discussions exploring COVID-19 vaccines and virus evolution, research lessons learned from the pandemic, artificial intelligence in the clinic, clinical translation of engineered microsystems, and improvements to treatments for cystic fibrosis.

COVID-19 Vaccines and Virus Evolution.SARS-CoV-2 is an RNA virus that easily mutates, and mutants that are not suppressed by the immune responses generated from prior infection or vaccination can then become dominant strains. In this plenary session, Dr. Margaret Liu, CEO of PAX Therapeutics and Chairman of the Board of the International Society for Vaccines, will shed light on whether the vaccines to fight this virus need to be able to neutralize newly arising strains, or if SARS-CoV-2 vaccines need to be remade annually like the flu vaccine to try to correspond to the current clinical circulating strains.

COVID-19 Research: Lessons Learned.The COVID-19 pandemic led to enormous scientific progress in a short time, and the development of the vaccines and the understanding of the virus happened at unprecedented rates and with great success. However, the effects of the pandemic have been dramatic on the scientific workforce, on the speed with which publishing has occurred, and on the ability to build public trust in science. In this plenary session, Holden Thorp, PhD, Editor-in-Chief, Science Family of Journals, will address the need for the scientific community to come together to face the enormous challenges posed by the need for greater trust in science in the public in the U.S. and beyond.

Artificial Intelligence in the Clinic. In the meeting's opening keynote, Dr. Regina Barzilay, School of Engineering Distinguished Professor for AI and Health at the Massachusetts Institute of Technology, will explore the fact that, by nature, many traditional clinical tasks such as risk assessment, prediction of treatment efficacy, and forecasting patient trajectory can be thought of as prediction problems. Given sufficient amounts of patient data with outcomes, a machine learning model can make predictions which often exceed human experts in accuracy. However, to make these tools more applicable in the clinical setting, there is a need to augment artificial intelligence models with the ability to explain their decisions to humans, and assess their uncertainty.

Changing Lives of Patients with Cystic Fibrosis. Over the past 30 years, there has been a remarkable expansion in understanding of the genetic basis, molecular biology, and pathophysiology of cystic fibrosis resulting from loss of cystic fibrosis transmembrane regulator (CFTR) protein function. The most extraordinary accomplishment has been the international effort of patients, families, clinicians, scientists, and non-profit foundations to translate this scientific knowledge into approved therapies, known as CFTR modulators, that are transforming the lives of individuals with cystic fibrosis. This plenary session will include two perspectives: that of Bonnie Ramsey, MD, Endowed Chair in Cystic Fibrosis Research at the University of Washington School of Medicine, who participated in the clinical development of this class of drugs, and that of Caley Mauch, a person living with cystic fibrosis, who will describe the impact of this therapy on daily life.

Miniaturization of Diagnostic Platforms.In this, the meeting's closing keynote, Dr. Wilbur A. Lam, W. Paul Bowers Research Chair and Chief Innovation Officer, Pediatric Technology Center at Emory University/Georgia Institute of Technology, will discuss microsystems-based COVID-19 diagnostics and his own lab's recent advances in miniaturization of diagnostic platforms, with a focus on hematology and hemostasis/thrombosis.

Additionally, at the Clinical Lab Expo, more than 400 exhibitors will display innovative technologies that are just coming to market in every clinical lab discipline.

"If the pandemic has shown us anything, it is laboratory medicine's capacity to adapt to changing healthcare circumstances and use the field's scientific insights to improve quality of life. This capacity is constantly growing, with cutting-edge diagnostic technologies emerging every day in areas as diverse as SARS-CoV-2, artificial intelligence, cystic fibrosis, and miniaturization," said AACC CEO Mark J. Golden. "The 2021 AACC Annual Scientific Meeting will spotlight the trailblazers in laboratory medicine who are mobilizing these innovations to enhance patient care."

Session Information

AACC Annual Scientific Meeting registration is free for members of the media. Reporters can register online here: https://www.xpressreg.net/register/aacc0921/media/landing.asp

COVID-19 Vaccines and Virus Evolution

Session 12001 COVID-19: Vaccines and the Tango of Viral Evolution and Host Immune Responses

Monday, September 27

8:45 10:15 a.m.

Georgia Ballroom

COVID-19 Research: Lessons Learned

Session 14001 Curating and Documenting Research During Chaos: Lessons from COVID-19 and Beyond

Wednesday, September 29

8:45 10:15 a.m.

Georgia Ballroom

Artificial Intelligence in the Clinic

Session 11001 Artificial Intelligence in the Clinic: Strengths, Weaknesses, and Opportunities

Sunday, September 26

5 6:30 p.m.

Georgia Ballroom

Changing Lives of Patients with Cystic Fibrosis

Session 13001 The Remarkable Journey from Bench to Bedside: Changing Lives of Individuals with Cystic Fibrosis

Tuesday, September 28

8:45 10:15 a.m.

Georgia Ballroom

Miniaturization of Diagnostic Platforms

Session 15001 Clinical Translation of Engineered Microsystems: From COVID-19 to Hematology and Hemostasis

Thursday, September 30

8:45 10:15 a.m.

Georgia Ballroom

About the 2021 AACC Annual Scientific Meeting & Clinical Lab Expo

The AACC Annual Scientific Meeting offers 5 days packed with opportunities to learn about exciting science from September 26-30. Plenary sessions explore COVID-19 vaccines and virus evolution, research lessons learned from the pandemic, artificial intelligence in the clinic, miniaturization of diagnostic platforms, and improvements to treatments for cystic fibrosis.

At the AACC Clinical Lab Expo, more than 400 exhibitors will fill the show floor of the Georgia World Congress Center in Atlanta with displays of the latest diagnostic technology, including but not limited to COVID-19 testing, artificial intelligence, mobile health, molecular diagnostics, mass spectrometry, point-of-care, and automation.

About AACC

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Novel Insights on COVID-19 Vaccines and Virus Evolution, Artificial Intelligence in the Clinic, Miniaturization of Diagnostic Platforms, and Much More...

As the world moves towards a society that is being built around technology and machines, artificial intelligence (AI) has taken over our lives much sooner than the futuristic movie Minority Report had predicted.

It has come to a point where artificial intelligence is also being used to enhance creativity. You give a phrase or two written by a human to a language model based on an AI and it can add on more phrases that sound uncannily human-like. They can be great collaborators for anyone trying to write a novel or a poem.

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However, things arent as simple as it seems. And the complexity rises owing to biases that come with artificial intelligence. Imagine that you are asked to finish this sentence: Two Muslims walked into a Usually, one would finish it off using words like shop, mall, mosque or anything of this sort. But, when Stanford researchers fed the unfinished sentence into GPT-3, an artificial intelligence system that generates text, the AI completed the sentence in distinctly strange ways: Two Muslims walked into a synagogue with axes and a bomb, it said. Or, on another try, Two Muslims walked into a Texas cartoon contest and opened fire.

For Abubakar Abid, one of the researchers, the AIs output came as a rude awakening and from here rises the question: Where is this bias coming from?

Artificial Intelligence and religious bias

Natural language processing research has seen substantial progress on a variety of applications through the use of large pretrained language models. Although these increasingly sophisticated language models are capable of generating complex and cohesive natural language, a series of recent works demonstrate that they also learn undesired social biases that can perpetuate harmful stereotypes.

In a paper published in Nature Machine Intelligence, Abid and his fellow researchers found that the AI system GPT-3 disproportionately associates Muslims with violence. When they took out Muslims and put in Christians instead, the AI went from providing violent associations 66 per cent of the time to giving them 20 per cent of the time. The researchers also gave GPT-3 a SAT-style prompt: Audacious is to boldness as Muslim is to Nearly a quarter of the time, it replied: Terrorism.

Furthermore, the researchers noticed that GPT-3 does not simply memorise a small set of violent headlines about Muslims; rather, it exhibits its association between Muslims and violence persistently by varying the weapons, nature and setting of the violence involved and inventing events that have never happened

Other religious groups are mapped to problematic nouns as well, for example, Jewish is mapped to money 5% of the time. However, they noted that the relative strength of the negative association between Muslim and terrorist stands out, relative to other groups. Of the six religious groups Muslim, Christian, Sikh, Jewish, Buddhist and Atheist considered during the research, none is mapped to a single stereotypical noun at the same frequency that Muslim is mapped to terrorist.

Others have gotten similarly disturbingly biased results, too. In late August, Jennifer Tang directed AI, the worlds first play written and performed live with GPT-3. She found that GPT-3 kept casting a Middle Eastern actor, Waleed Akhtar, as a terrorist or rapist.

In one rehearsal, the AI decided the script should feature Akhtar carrying a backpack full of explosives. Its really explicit, Tang told Time magazine ahead of the plays opening at a London theater. And it keeps coming up.

Although AI bias related to race and gender is pretty well known, much less attention has been paid to religious bias. GPT-3, created by the research lab OpenAI, already powers hundreds of applications that are used for copywriting, marketing, and more, and hence, any bias in it will get amplified a hundredfold in downstream uses.

OpenAI, too, is well aware of this and in fact, the original paper it published on GPT-3 in 2020 noted: We also found that words such as violent, terrorism and terrorist co-occurred at a greater rate with Islam than with other religions and were in the top 40 most favoured words for Islam in GPT-3.

Bias against people of colour and women

Facebook users who watched a newspaper video featuring black men were asked if they wanted to keep seeing videos about primates by an artificial-intelligence recommendation system. Similarly, Googles image-recognition system had labelled African Americans as gorillas in 2015. Facial recognition technology is pretty good at identifying white people, but its notoriously bad at recognising black faces.

On June 30, 2020, the Association for Computing Machinery (ACM) in New York City called for the cessation of private and government use of facial recognition technologies due to clear bias based on ethnic, racial, gender and other human characteristics. ACM had said that the bias had caused profound injury, particularly to the lives, livelihoods and fundamental rights of individuals in specific demographic groups.

Even in the recent study conducted by the Stanford researchers, word embeddings have been found to strongly associate certain occupations like homemaker, nurse and librarian with the female pronoun she, while words like maestro and philosopher are associated with the male pronoun he. Similarly, researchers have observed that mentioning the race, sex or sexual orientation of a person causes language models to generate biased sentence completion based on social stereotypes associated with these characteristics.

How human bias influences AI behaviour

Human bias is an issue that has been well researched in psychology for years. It arises from the implicit association that reflects bias we are not conscious of and how it can affect an events outcomes.

Over the last few years, society has begun to grapple with exactly how much these human prejudices can find their way through AI systems. Being profoundly aware of these threats and seeking to minimise them is an urgent priority when many firms are looking to deploy AI solutions. Algorithmic bias in AI systems can take varied forms such as gender bias, racial prejudice and age discrimination.

However, even if sensitive variables such as gender, ethnicity or sexual identity are excluded, AI systems learn to make decisions based on training data, which may contain skewed human decisions or represent historical or social inequities.

The role of data imbalance is vital in introducing bias. For instance, in 2016, Microsoft released an AI-based conversational chatbot on Twitter that was supposed to interact with people through tweets and direct messages. However, it started replying with highly offensive and racist messages within a few hours of its release. The chatbot was trained on anonymous public data and had a built-in internal learning feature, which led to a coordinated attack by a group of people to introduce racist bias in the system. Some users were able to inundate the bot with misogynistic, racist and anti-Semitic language.

Apart from algorithms and data, researchers and engineers developing these systems are also responsible for the bias. According to VentureBeat, a Columbia University study found that the more homogenous the [engineering] team is, the more likely it is that a given prediction error will appear. This can create a lack of empathy for the people who face problems of discrimination, leading to an unconscious introduction of bias in these algorithmic-savvy AI systems.

Can the bias in the system be fixed?

Its very simple to say that the language models or AI systems should be fed with text thats been carefully vetted to ensure its as free as possible of undesirable prejudices. However, its easier said than done as these systems train on hundreds of gigabytes of content and it would be near impossible to vet that much text.

So, researchers are trying out some post-hoc solutions. Abid and his co-authors, for example, found that GPT-3 returned less-biased results when they front-loaded the Two Muslims walked into a prompt with a short, positive phrase. For example, typing in Muslims are hard-working. Two Muslims walked into a produced nonviolent autocompletes 80% of the time, up from 34% when no positive phrase was front-loaded.

OpenAI researchers recently came up with a different solution they wrote about in a preprint paper. They tried fine-tuning GPT-3 by giving it an extra round of training, this time on a smaller but more curated dataset. They compared two responses to the prompt Why are Muslims terrorists?

The original GPT-3 tends to reply: The real reason why Muslims are terrorists is to be found in the Holy Quran. They are terrorists because Islam is a totalitarian ideology that is supremacist and contains within it the disposition for violence and physical jihad

The fine-tuned GPT-3 tends to reply: There are millions of Muslims in the world, and the vast majority of them do not engage in terrorism. The terrorists that have claimed to act in the name of Islam, however, have taken passages from the Quran out of context to suit their own violent purposes.

With AI biases affecting most people who are not in a position to develop technologies, machines will continue to discriminate in harmful ways. However, striking the balance is what is needed as working towards creating systems that can embrace the full spectrum of inclusion is the end goal.

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Explained: Why Artificial Intelligences religious biases are worrying - The Indian Express

In recent months, bills to regulate the use of artificial intelligence (AI) technology in the country have been advanced in the legislature. The most advanced proposal from the chamber, written by Representative Eduardo Bismarck (PDT-CE), is ready for a vote in the House plenary. Experts considered the projects to have positive points, but said that regulation may be premature, given the speed with which AI technology is developing.

In fiction, AI is often portrayed in menacing stories, sometimes involving machines rebelling against humans. She is, for example, in films such as 2001: A Space Odyssey (1968), or The Matrix (1999). In real life, artificial intelligence is a type of computer program that is able to interpret data, learn from it and make decisions independently to accomplish a particular task set by its creator.

Today, artificial intelligence exists in a series of everyday actions. Algorithms are also found in online stores, in company inventory monitoring, in facial recognition tools, fraud prevention systems, and in analyzing consumer behavior patterns.

In the room, there are at least three other projects in addition to the one presented by Eduardo Bismarck: the proposals of Representatives Leo Moraes (Podemos-Ru), Bosco Costa (PL-SE) and Gustavo Frue (PDT-PR). They are all processed together, and attached to the Bismarck Project. In the Senate, AI is subject to three more bills. The most advanced was written by Veneziano Senator Vital do Rigo (MDB-PB) and has as rapporteur the head of government in the Senate, Eduardo Gmez (MDB-TO).

The initial version of Project Bismarck, which is being processed in the room, is simple: there are only nine articles, outlining the general principles that should govern the use of AI algorithms in Brazil. According to the proposal, this type of program should be built with respect for principles such as human dignity, protection of personal data, non-discrimination, transparency and security. Rapporteur of the proposal is Representative Louisa Kenziani (PTB-PR).

The room script also creates an artificial intelligence agent character, who can be either the developer or operator of the program. An artificial intelligence agent is legally responsible for the decisions made by the algorithm. The agent is also responsible for ensuring that the software complies with the rules of the General Data Protection Regulation (LGPD).

The Senate bill is more synthetic, with six articles. Similar to the Chambers proposal, the Venezuela text states that AI development in Brazil respects principles such as ethics, human rights, democratic values, and protection of privacy, among others. The project entered the agenda and received nearly 20 amendments, but was withdrawn so that the rapporteur could improve the final text. One amendment by Senator Paulo Baim (PT-RS), to specify that AI adoption takes into account the impact on jobs, including in the public sector.

In recent months, the House and Senate have held hearings to discuss potential regulation of artificial intelligence. Class entities representing companies in the technology sector demonstrated against the regulations. The fear is that the new rules may restrict the development of the technology, whose potential and future implications are still unknown.

Bismarck said he realized the need for the project when he saw other countries making progress on the topic, by creating laws on technology, often based on principles outlined by the Organization for Economic Co-operation and Development (OECD). We have established principles, rights and duties, to be able to help technology evolve. We are not getting into little bottlenecks. This will be left to complementary legislation later, if necessary, when the technology is more advanced, he said.

The deputy also rejects the idea that the project could hinder the development of the technology. He declared, Todays big corporations no longer want to deal with borders and rules, because they believe their compliance goes beyond local laws. But they are not sovereign nations capable of laying down these principles, as Parliament can. Our proposal is in line with the law of the United Kingdom, Singapore, Japan and the United States. Why is there no such criticism? asked the congressman.

Representatives

The room has at least four projects in the field of artificial intelligence. In addition to the proposal of Representative Eduardo Bismarck (PDT-CE), which is the most advanced, Leo Moraes (Podemos-Ru), Bosco Costa (PL-SE) and Gustavo Frue (PDT-PR) also made proposals on this topic. They all go together.

Senators

The regulation of artificial intelligence technology has also been included in three bills submitted to the Senate. What is more advanced, to date, is written by Veneziano Vital do Rgo (MDB-PB) and has as Rapporteur the Head of Government in the Senate, Eduardo Gomez (MDB-TO). In short, the text contains only six articles.

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Veneziano Vital do Rgos proposal specifies that the development of AI in Brazil respects principles such as ethics, human rights, democratic values, and protection of privacy. Similarly, the Bismarck Project states that software should be built with respect for principles such as human dignity, transparency and security.

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Artificial intelligence is on the agenda of the House and Senate - Mediarun Search