The Prometheus League
Breaking News and Updates
- Abolition Of Work
- Ai
- Alt-right
- Alternative Medicine
- Antifa
- Artificial General Intelligence
- Artificial Intelligence
- Artificial Super Intelligence
- Ascension
- Astronomy
- Atheism
- Atheist
- Atlas Shrugged
- Automation
- Ayn Rand
- Bahamas
- Bankruptcy
- Basic Income Guarantee
- Big Tech
- Bitcoin
- Black Lives Matter
- Blackjack
- Boca Chica Texas
- Brexit
- Caribbean
- Casino
- Casino Affiliate
- Cbd Oil
- Censorship
- Cf
- Chess Engines
- Childfree
- Cloning
- Cloud Computing
- Conscious Evolution
- Corona Virus
- Cosmic Heaven
- Covid-19
- Cryonics
- Cryptocurrency
- Cyberpunk
- Darwinism
- Democrat
- Designer Babies
- DNA
- Donald Trump
- Eczema
- Elon Musk
- Entheogens
- Ethical Egoism
- Eugenic Concepts
- Eugenics
- Euthanasia
- Evolution
- Extropian
- Extropianism
- Extropy
- Fake News
- Federalism
- Federalist
- Fifth Amendment
- Fifth Amendment
- Financial Independence
- First Amendment
- Fiscal Freedom
- Food Supplements
- Fourth Amendment
- Fourth Amendment
- Free Speech
- Freedom
- Freedom of Speech
- Futurism
- Futurist
- Gambling
- Gene Medicine
- Genetic Engineering
- Genome
- Germ Warfare
- Golden Rule
- Government Oppression
- Hedonism
- High Seas
- History
- Hubble Telescope
- Human Genetic Engineering
- Human Genetics
- Human Immortality
- Human Longevity
- Illuminati
- Immortality
- Immortality Medicine
- Intentional Communities
- Jacinda Ardern
- Jitsi
- Jordan Peterson
- Las Vegas
- Liberal
- Libertarian
- Libertarianism
- Liberty
- Life Extension
- Macau
- Marie Byrd Land
- Mars
- Mars Colonization
- Mars Colony
- Memetics
- Micronations
- Mind Uploading
- Minerva Reefs
- Modern Satanism
- Moon Colonization
- Nanotech
- National Vanguard
- NATO
- Neo-eugenics
- Neurohacking
- Neurotechnology
- New Utopia
- New Zealand
- Nihilism
- Nootropics
- NSA
- Oceania
- Offshore
- Olympics
- Online Casino
- Online Gambling
- Pantheism
- Personal Empowerment
- Poker
- Political Correctness
- Politically Incorrect
- Polygamy
- Populism
- Post Human
- Post Humanism
- Posthuman
- Posthumanism
- Private Islands
- Progress
- Proud Boys
- Psoriasis
- Psychedelics
- Putin
- Quantum Computing
- Quantum Physics
- Rationalism
- Republican
- Resource Based Economy
- Robotics
- Rockall
- Ron Paul
- Roulette
- Russia
- Sealand
- Seasteading
- Second Amendment
- Second Amendment
- Seychelles
- Singularitarianism
- Singularity
- Socio-economic Collapse
- Space Exploration
- Space Station
- Space Travel
- Spacex
- Sports Betting
- Sportsbook
- Superintelligence
- Survivalism
- Talmud
- Technology
- Teilhard De Charden
- Terraforming Mars
- The Singularity
- Tms
- Tor Browser
- Trance
- Transhuman
- Transhuman News
- Transhumanism
- Transhumanist
- Transtopian
- Transtopianism
- Ukraine
- Uncategorized
- Vaping
- Victimless Crimes
- Virtual Reality
- Wage Slavery
- War On Drugs
- Waveland
- Ww3
- Yahoo
- Zeitgeist Movement
-
Prometheism
-
Forbidden Fruit
-
The Evolutionary Perspective
Category Archives: Artificial Intelligence
Which Industries are Hiring AI and Machine Learning Roles? – Dice Insights
Posted: June 28, 2021 at 10:18 pm
Companies everywhere are pouring resources into artificial intelligence (A.I.) and machine learning (ML) initiatives. Many technologists believe that apps smartened with A.I. and ML tools will eventually offer better customer personalization; managers hope that A.I. will lead to better data analysis, which in turn will power better business strategies.
But which industries are actually hiring A.I. specialists? If you answer that question, it might give you a better idea of where those resources are being deployed. Fortunately,CompTIAs latest Tech Jobs Reportoffers a breakdown of A.I. hiring, using data from Burning Glass, which collects and analyzes millions of job postings from across the country. Check it out:
Perhaps its no surprise that manufacturing tops this list; after all, manufacturers have been steadily automating their production processes for years, and it stands to reason that they would turn to A.I. and ML to streamline things even more. In theory, A.I. will also help manufacturers do everythingfrom reducing downtime to improving supply chainsalthough it may take some time to get the models right.
The presence of healthcare, banking, and public administration likewise seem logical.These three industries have the money to invest in A.I. and ML right now and have the greatest opportunity to see the investment pay off, fast, Gus Walker, director of product at Veritone, an A.I. tech company based in Costa Mesa, California,told Dicelate last year.That being said, the pandemic has caused industries hit the hardest to take a step back and look at how they can leverage AI and ML to rebuild or adjust in the new normal.
Compared to overall tech hiring, the number of A.I.-related job postings is still relatively small. Right now, mastering and deploying A.I. and machine learning is something of a specialist industry; but as these technologies become more commodified, and companies develop tools that allow more employees to integrate A.I. and ML into their projects, the number of job postings for A.I. and ML positions could increase over the next several years. Indeed, one IDC report from 2020 found three-quarters of commercial enterprise applications could lean on A.I. in some way by2021.
Its also worth examining where all that A.I. hiring is taking place; its interesting that Washington DC tops this particular list, with New York City a close second; Silicon Valley and Seattle, the nations other big tech hubs, are somewhat further behind, at least for the moment. Washington DC is notable not only for federal government hiring, but the growing presence of companies such as Amazon that hunger for talent skilled in artificial intelligence:
Jobs that leverage artificial intelligence are potentially lucrative, with a current median salary (according to Burning Glass)of $105,000. Its also a skill-set thatmore technologists may need to become familiar with, especially managers and executives.A.I. is not going to replace managers but managers that use A.I. will replace those that do not, Rob Thomas, senior vice president of IBMscloudand data platform,recently told CNBC. If you mention A.I. or ML on your resume and applications, make sure you know your stuff before the job interview; chances are good youll be tested on it.
Want more great insights?Create a Dice profile today to receive the weekly Dice Advisor newsletter, packed with everything you need to boost your career in tech. Register now
See the rest here:
Which Industries are Hiring AI and Machine Learning Roles? - Dice Insights
Posted in Artificial Intelligence
Comments Off on Which Industries are Hiring AI and Machine Learning Roles? – Dice Insights
Artificial Intelligence Restores Mutilated Rembrandt Painting The Night Watch – ARTnews
Posted: at 10:18 pm
One of Rembrandts finest works, Militia Company of District II under the Command of Captain Frans Banninck Cocq (better known as The Night Watch) from 1642, is a prime representation of Dutch Golden Age painting. But the painting was greatly disfigured after the artists death, when it was moved from its original location at the Arquebusiers Guild Hall to Amsterdams City Hall in 1715. City officials wanted to place it in a gallery between two doors, but the painting was too big to fit. Instead of finding another location, they cut large panels from the sides as well as some sections from the top and bottom. The fragments were lost after removal.
Now, centuries later, the painting has been made complete through the use of artificial intelligence. The Rijksmuseum in the Netherlands has owned The Night Watch since it opened in 1885 and considers it one of the best-known paintings in its collection. In 2019, the museum embarked on a multi-year, multi-million-dollar restoration project, referred to as Operation Night Watch, to recover the painting. The effort marks the 26th restoration of the work over the span of its history.
In the beginning, restoring The Night Watch to its original size hadnt been considered until the eminent Rembrandt scholar Erst van der Wetering suggested it in a letter to the museum, noting that the composition would change dramatically. The museum tapped its senior scientist, Rob Erdmann, to head the effort using three primary tools: the remaining preserved section of the original painting, a 17th-century copy of the original painting attributed to Gerrit Lundens that had been made before the cuts, and AI technology.
About the decision to use AI to reconstruct the missing pieces instead of commissioning an artist to repaint the work, Erdmann told ARTnews, Theres nothing wrong with having an artist recreate [the missing pieces] by looking at the small copy, but then wed see the hand of the artist there. Instead, we wanted to see if we could do this without the hand of an artist. That meant turning to artificial intelligence.
AI was used to solve a set of specific problems, the first of which was that the copy made by Lundens is one-fifth the size of the original, which measures almost 12 feet in length. The other issue was that Lundens painted in a different style than Rembrandt, which raised the question of how the missing pieces could be restored to an approximation of how Rembrandt would have painted them. Erdmann created three separate neural networks, a type of machine learning technology that trains computers to learn how to do specific tasks to address the problems.
The first [neural network] was responsible for identifying shared details. It found more than 10,000 details in common between The Night Watch and Lundenss copy. For the second, Erdmann said, Once you have all of these details, everything had to be warped into place, essentially by tinkering with the pieces by scoot[ing one part] a little bit to the left and making another section of the painting 2 percent bigger, and rotat[ing another] by four degrees. This way all the details would be perfectly aligned to serve as inputs to the third and final stage. Thats when we sent the third neural network to art school.
Erdmann made a test for the neural network, similar to flashcards, by splitting up the painting into thousands of tiles and placing matching tiles from both the original and the copy side-by-side. The AI then had to create an approximation of those tiles in the style of Rembrandt. Erdmann graded the approximationsand if it painted in the style of Lundens, it failed. After the program ran millions of times, the AI was ready to reproduce tiles from the Lundens copy in the style of Rembrandt.
The AIs reproduction was printed onto canvas and lightly varnished, and then the reproduced panels were attached to the frame of The Night Watch over top the fragmented original. The reconstructed panels do not touch Rembrandts original painting and will be taken down in three months out of respect for the Old Master. It already felt to me like it was quite bold to put these computer reconstructions next to Rembrandt, Erdmann said.
As for the original painting by Rembrandt, it may receive conservation treatment depending on the conclusions of the research being conducted as part of Operation Night Watch. The painting has sustained damaged that may warrant additional interventions. In 1975, the painting was slashed several times, and, in 1990, it was splashed with acid.
The reconstructed painting went on view at the Rijksmuseum on Wednesday and will remain into September.
Continued here:
Artificial Intelligence Restores Mutilated Rembrandt Painting The Night Watch - ARTnews
Posted in Artificial Intelligence
Comments Off on Artificial Intelligence Restores Mutilated Rembrandt Painting The Night Watch – ARTnews
Banking on AI: The Opportunities and Limitations of Artificial Intelligence in the Fight Against Financial Crime and Money Laundering – International…
Posted: at 10:18 pm
By Justin Bercich, Head of AI, Lucinity
Financial crime has thrived during the pandemic. It seems obvious that the increase in digital banking, as people were forced to stay inside for months on end, would correlate with a sharp rise in money laundering (ML) and other nefarious activity, as criminals exploited new attack surfaces and the global uncertainty caused by the pandemic.
But, when you consider that fines for money-laundering violations have catapulted by 80% since 2019, you begin to realise just how serious and widespread the situation is. Consequently, the US Government is making strides to re-write its anti-money laundering (AML) rulebook, having enacted its first major piece of AML legislation since 2004 earlier this year.New secretary of the treasury Janet Yellen, with her decades of financial regulation experience, adds further credence to the fact the AML sector is primed for more significant reform in the coming months and years.
Yet, despite the positives and promises of technological innovation in the AML space, there still remains great debate and scepticism about the ethics and viability of incorporating artificial intelligence (AI) and machine learning deeply into banks and the broader financial ecosystem. What are the opportunities and limitations of AI, and how can we ensure its application remains ethical for all?
Human AI A banks newest investigator
While AI isnt a new asset in the fight against financial crime, Human AI is a ground-breaking application that has the potential to drastically improve compliance programs among forward-thinking banks. Human AI is all about bringing together the best tools and capabilities of people and machines. Together, human and machine help one another unearth important insights and intelligence at the exact point when key decisions need to be made forming the perfect money laundering front-line investigator and drastically improve productivity in AML.
The most powerful aspect of Human AI is that its a self-fulfilling cycle. Insights are fed back into the machine learning model, so that both human and technology improve. After all, the more the technology improves, the more the human trusts it. As we gain trust in technology we feed more relevant human-led insights back into the machine, ultimately resulting in a flowing stream of synergies that strengthens the Human-AI nexus, therefore empowering users and improving our collective defenses against financial crime. That is Human AI.
An example of this in action is Graph Data Science (GDS) an approach that is capable of finding hidden relationships in financial transaction networks. The objective of money launderers is to hide in plain sight, while AML systems are trying to uncover the hidden connections between a seemingly normal person/entity and a nefarious criminal network. GDS helps uncover these links, instead of relying on a human to manually trawl through a jungle of isolated spreadsheets with thousands of fields.
Human AI brings us all together
Whats more, a better understanding of AI doesnt just benefit the banks and financial institutions wielding its power on the frontline, it also strengthens the relationship between bank and regulator. Regulatorus need to understand why a decision has been made by AI in order to determine its efficacy and with Human AI becoming more accessible and transparent (and, therefore, human), banks can ensure machine-powered decisions are repeatable, understandable, and explainable.
This is otherwise known as Explainable AI, meaning investigators, customers, or any user of an AI system have the ability to see and interact with data that is logical, explainable and human. Not only does this help build a bridge of trust between humans and machines, but also between banks and regulators, ultimately leading to better systems of learning that help improve one another over time.
This collaborative attitude should also be extended to the regulatory sandbox, a virtual playground where fintechs and banks can test innovative AML solutions in a realistic and controlled environment overseen by the regulators. This prevents brands from rushing new products into the market without the proper due diligence and regulatory frameworks in place.
Known as Sandbox 2.0, this approach represents the future of policy making, giving fintechs the autonomy to trial cutting-edge Human AI solutions that tick all the regulatory boxes, and ultimately result in more sophisticated and effective weapons in the fight against financial crime and money laundering.
Overhyped or underused? The limitations of AI
Anti-money laundering technology has, in many ways, been our last line of defence against financial crime in recent years a dam that is ready to burst at any moment. Banks and regulators are desperately trying to keep pace with the increasing sophistication of financial criminals and money launderers. New methods for concealing illicit activity come to surface every month, and technological innovation is struggling to keep up.
This is compounded by our need to react quicker than ever before to new threats. This leaves almost no room for error, and often not enough time to exercise due diligence and ethical considerations. Too often, new AI and machine learning technologies are prematurely hurried out into the market, almost like rushing soldiers to the front line without proper training.
Increasing scepticism around AI is understandable, given the marketing bonanza of AI as a panacea to growth. Banks that respect the opportunities and limitations of AI will use the technology to focus more on efficiency gains and optimization, allowing AI algorithms to learn and grow organically, before looking to extract deeper intelligence used to driverevenue growth. It is a wider business lesson that can easily be applied to AI adoption: banks must learn their environment, capabilities, and limitations beforemastering a task.
What banks must also remember is that AI experimentation comes withdiminishing returns. They should focus on executing strategic, production-readyAI micro-projects in parallel with human teams to deliver actionable insights and value. At the same time, this technology can be trained to learn from interactions with their human colleagues.
But technology cant triumph alone
Application of AI and machine learning is now being used across most major aspects of the financial ecosystem, areas that have traditionally been people-focussed, such as issuing new products, performing compliance functions, and customer service. This requires an augmentation of thinking, where human and AI work alongside one another to achieve a common goal, rather than just throwing an algorithm at the problem.
But of course, we must recognise that this technology cant win the fight in isolation. This isnt the time to keep our cards close to our chests the benefits of AI against financial crime and ML must be made accessible to everyone affected.
Data must be tracked across all vendors and along the entire supply chain, from payments processors to direct integrations. And, the AI technology being used to enable near-real time information sharing must go both ways: from bank to regulator and back again. Only then suspicious activity can be analysed effectively, meaning everyone can trust the success of AI.
Over the next few years, the potential of Human AI will be brought to life. Building trust between one another is crucial to addressing blackbox concerns, along with consistent training of AI and machines to become more human in their output, which will ultimately make all our lives more fulfilling.
Go here to read the rest:
Posted in Artificial Intelligence
Comments Off on Banking on AI: The Opportunities and Limitations of Artificial Intelligence in the Fight Against Financial Crime and Money Laundering – International…
How to Invest in Robotics and Artificial Intelligence – Analytics Insight
Posted: at 10:18 pm
We frequently put robotics and artificial intelligence together, but they are two separate fields. The robotics and artificial intelligence industries are some of the largest markets in the tech space today. Almost every industry in the world is adopting these technologies to boost growth and increase customer engagement.
According to reports, the global robotics market is expected to grow up to US$158.21 billion, between the period 2018 to 2025, at a CAGR of 19.11%. This growth is connected to the increasing adoption of artificial intelligence and robotics technology. Between 2020 to 2025, the market will grow at a CAGR of 25.38%.
During the pandemic, the demand for robotics technology has increased drastically. The medical field is deploying surgical robots to fight against Covid-19. Robots are helping healthcare professionals and patients by delivering food and medications, measuring the vitals, and aiding social distancing.
The automation industry is also using robotics technology to drive growth and transformation. Other industries like food, defense, manufacturing, retail, and others are also deploying robotics.
According to the reports, the global AI market is expected to grow from US$58.3 billion in 2021 to US$309.6 billion by 2026. Among the many factors that will drive the growth in the artificial intelligence market, the Covid-19 pandemic is the chief reason.
The pandemic has encouraged new applications and technological advancements in the market. Industries like healthcare, food, and manufacturing are increasingly adopting AI technologies to promote efficiency in business operations. Big tech companies like Microsoft, IBM, and Google are deploying AI to facilitate drug development, remote communication between patients and healthcare providers, and other services. AI-powered machines are also helping educators to track students performances, bridging the gaps in teaching techniques, and automating laborious administrative tasks.
Share This ArticleDo the sharing thingy
See the original post:
How to Invest in Robotics and Artificial Intelligence - Analytics Insight
Posted in Artificial Intelligence
Comments Off on How to Invest in Robotics and Artificial Intelligence – Analytics Insight
Acceleration of Artificial Intelligence in the Healthcare Industry – Analytics Insight
Posted: at 10:18 pm
Healthcare Industry Leverages Artificial Intelligence
With the continuous evolvement of Artificial Intelligence, the world is being benefited to the utmost level, as the applications of Artificial Intelligence is unremitting. This technology can be operated in any sector of industry, including the healthcare industry.The advancement of technology and the AI (Artificial Intelligence), as a part of modern technology have resulted in the formation of a digital macrocosm. Artificial Intelligence, to be precise, is a programming where, there is a duplication of human intelligence incorporated in the machines and it works and acts like a human.
Artificial Intelligence is transmuting the system and methods of the healthcare industries. Artificial Intelligence and healthcare, were found together over half a century. The healthcare industries use Natural Language Process to categorise certain data patterns.Natural Language Process is the process of giving a computer, the ability to understand text and spoken words just like the same way human beings can. In the healthcare sector, it gives the effect to the clinical decision support. The natural language process uses algorithms that can mimic like human responses to conversation and queries. This NLP, just like a human can take the form of simulated mediator using algorithms to connect to the health plan members.
Artificial Intelligence can be used by the clinical trials, to hasten the searches and validation of medical coding. This can help reduce the time to start, improve and accomplish clinical trainings. In simple words medical coding is transmitting medial data about a patient into alphanumeric code.
Clinical Decisions All the healthcare sectors are overwhelmed with gigantic volumes of growing responsibility and health data. Machine learning technologies as a part of Artificial Intelligence, can be applied to the electronic health records, with the help of this the clinical professionals can hunt for proper, error-free, confirmation-based statistics that has been cured by medical professionals. Further, Natural Language Process just like the chatbots, can be used for everyday conversation where it allows the users to type questions as if they are questioning a medical professional and receive fast and unfailing answers.
Health Equity Artificial Intelligence and Machine learning algorithms can be used to reduce bias in this sector by promoting diversities and transparency in data to help in the improvement of health equity.
Medication Detection Artificial Intelligence can be used by the pharma companies, to deal with drug discoveries and thus helping in reducing the time to determine and taking drugs all the way to the market. Machine Learning and Big Data as a part of Artificial Intelligence do have the great prospective to cut down the value of new medications.
Pain Management With the help of Artificial Intelligence and by creating replicated veracities the patients can be easily distracted from their existing cause of pain. Not only this, the AI can also be incorporated for the for the help of narcotic crisis.
System Networked Infirmaries Unlike now, one big hospital curing all kind of diseases can be divided into smaller pivots and spokes, where all these small and big clinics will be connected to a single digital framework. With the help of AI, it can be easy to spot patients who are at risk of deterioration.
Medical Images and Diagnosis The Artificial Intelligence alongside medical coding can go through the images and X-rays of the body to identify the system of the diseases that is to be treated. Further Artificial Intelligence technology with the help of electronic health records is used in healthcare industry that allows the cardiologists to recognize critical cases first and give diagnosis with accuracy and potentially avoiding errors.
Health Record Analysing With the advance of Artificial Intelligence, now it is easy for the patients as well as doctors to collect everyday health data. All the smart watches that help to calculate heart rates are the best example of this technology.
This is just the beginning of Artificial Intelligence in the healthcare industry. Making a start from Natural Language process, Algorithms and medical coding, imaging and diagnosis, there is a long way for the Artificial Intelligence to be capable of innumerable activities and to help medical professionals in making superior decisions. The healthcare industry is now focusing on technological innovation in serving to its patients. The Artificial Intelligence have highly transmuted the healthcare industry, thus resulting in development in patient care.
Share This ArticleDo the sharing thingy
See more here:
Acceleration of Artificial Intelligence in the Healthcare Industry - Analytics Insight
Posted in Artificial Intelligence
Comments Off on Acceleration of Artificial Intelligence in the Healthcare Industry – Analytics Insight
Artificial Intelligence Platform Provider ASAPP Raises $120 Million to Drive Greater Performance of Customer Experience (CX) Teams – PRNewswire
Posted: May 20, 2021 at 5:07 am
ASAPP is one of the few companies advancing research and development in artificial intelligence
"ASAPP is one of the few companies advancing research and development in artificial intelligence and its application for customer experience. In an environment where customer expectations are rising, ASAPP is helping large enterprises advance digital engagement, real-time voice transcription, speech analytics, and live agent coaching and analytics," said Gustavo Sapoznik, ASAPP founder and CEO. "The Customer Experience (CX) industry is at a crossroads. After years of interactive voice response systems (IVR) and bot investments, customer satisfaction is down, and costs have increased. We apply our AI research to make people in contact centers wildly more productive because existing rules-based technology and architectures limit companies to small improvements that can't bridge the digital transformation opportunity that AI is enabling and delivering."
"ASAPP's growth doubled last year, as we continue to deliver for customers like JetBlue and DISH Network with automation that supports both agents and agent-less interactions with their customers," said Tim Stone, ASAPP's Chief Operating Officer and Chief Financial Officer. "This Series C financing will enable ASAPP to increase investment in ASAPP's AI Native, Customer Experience Performance (CXP) platformthat helps global enterprise customers drive differentiated customer experiences, revenue, cost reductions and automation designed to support employees in customer serviceand sales."
Jason Green, founder of Emergence Capital who joined the ASAPP board recently said: "ASAPP is leading the way with the world's best AI talent and technology to help global enterprises dramatically improve customer experience, reduce costs and drive sales in a trillion-dollar market. By marrying human creativity, intelligence and empathy with artificial intelligence, the company is arming businesses with a next generation of productivity applications that every business at scale will eventually need to adopt."
ASAPP builds AI-Native products to solve problems of massive scale and inefficiency. With theCustomer Experience Performance (CXP) platformcontact centers can create better experiences and handle more customer engagement volume in less time, while consumers enjoy faster resolution to their needs.
About ASAPPASAPP is a research-based artificial intelligence software provider that solves large, complex, data-rich problems with AI-Native technology. Large enterprises use ASAPP to make customer experience teams highly productive and effective by augmenting human activity and automating the world's workflows. The company has offices in New York, Silicon Valley, Buenos Aires, London, and Bozeman. Visithttps://www.asapp.com for more information.
SOURCE ASAPP
Read the rest here:
Posted in Artificial Intelligence
Comments Off on Artificial Intelligence Platform Provider ASAPP Raises $120 Million to Drive Greater Performance of Customer Experience (CX) Teams – PRNewswire
Artificial intelligence and privacy rights: Daily Star columnist – The Straits Times
Posted: at 5:07 am
DHAKA (THE DAILY STAR/ASIA NEWS NETWORK) - Nobel Prize-winning author Kazuo Ishiguro's latest novel Klara And The Sun, his first since receiving the award in literature in 2017, has some relevance for policymakers and ordinary citizens across the globe.
The main protagonist in this dystopian science fiction story is Klara, an artificial friend (AF) - a human-like teenager who behaves and thinks almost like her cohort of the same age and is a fast learner, as any device or robot using artificial intelligence (AI) can be expected to be.
However, what we also learn is that if robots, even if they are super-intelligent, are allowed to make decisions that affect the lives of humans, it might lead to unintended consequences unless there are strict guidelines protecting privacy and other individual rights.
Many discerning readers might already be aware that AI is whipping up quite a storm, particularly as it makes inroads into facial recognition software, law enforcementand hiring decisions in the corporate world.
Policymakers in many countries are alarmed, realising the pros as well as the cons of this revolutionary technology.
The European Union, which has been at the forefront of safeguarding privacy rights, unveiled strict regulations last month to govern the use of AI, a first-of-its-kind policy that outlines how companies and governments can use AI technology, also known as "machine learning".
While these new rules are yet to be implemented and are still on the drawing boards, their impact will be similar to that of the General Data Protection Regulation (GDPR), which was drawn up to keep global technology companies such as Amazon, Google, Facebook and Microsoft in check.
The EU has been the world's most aggressive watchdog of the technology industry, with its policies often used as blueprints by other nations.
As mentioned, the bloc has already enacted the world's most far-reaching data privacy regulation, the GDPR, and is debating additional antitrust and content-moderation laws.
"We have to be aware that GDPR is not made for blockchain, facial or voice recognition, text and data mining... artificial intelligence," said Mr Axel Voss, a German member of the European Parliament and one of the creators of GDPR.
AI, in simple terms, is a computer programthat enables the machine to learn how to mimic the problem-solving and decision-making capabilities of the human mind.
An AI-enabled device learns how to respond to certain situations and uses algorithms and historical data to recognise a face, predict the weather or support a search engine like Google.
AI is playing a critical role in autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art, playing games (such as chess or Go), search engines, online assistants (such as Siri), image recognition in photographs, spam filtering, predicting flight delays and much more.
Large technology companies have poured billions of dollars into developing AI, as also have scores of others that use it to develop medicine, underwrite insurance policies and judge creditworthiness.
Governments use versions of AI in criminal justice and in allocating public services like income support.
The potential for AI is enormous, and here is the rub. To what extent can machines be manipulated to gain financial or strategic advantage by those who fund this research or manufacture them?
Are they really neutral? Can machines adapt to the humans they interactwith, or do existing biases become hardwired?
Facial recognition algorithms have been at the centre of privacy and ethics debates. Imagine a scenario where a government buys facial recognition software and uses it to track attendees during protest marches.
In Hong Kong, the police used a system, created by Israeli company Cellebrite, to access the phones of 4,000 protesters.
A researcher at an AI global conference claimed to be able to generate faces - including aspects of a person's age, gender and ethnicity - based on voices.
Digital rights groups across the United States, Britain and the EU have already raised many issues prompted by advances in AI research, and these include privacy violations, ethical concernsand lack of human control over AI.
Ms Ria Kalluri, a machine-learning scientist at Stanford University in California, said: "Because training data are drawn from human output, AI systems can end up mimicking and repeating human biases, such as racism and sexism."
Ms Kalluri urged her colleagues to dedicate more efforts into tackling scientific questions that make algorithms more transparent and create ways for non-experts to challenge a model's inner workings.
This controversy brings to the fore the role humans play in training the machines. We each have our biases and preferences, and the machines may inherit them.
There is increasing support to "debias the algorithms".
University College Dublin cognitive scientistAbeba Birhane, citing uses of AI in hiring and surveillance, said:"Algorithms exclude older workers, trans people, immigrants, children."
AI had already evoked criticisms from the late Professor Stephen Hawking, one of Britain's pre-eminent scientists, and billionaire entrepreneur Elon Musk has also raised a red flag.
Having said that, it cannot be gainsaid that the AI revolution is here and has come to stay.
The important question is, how do we harness the power of AI and manage its negative influence?
On the positive side, research has conclusively proven that AI is at least as good as humans in determining medical diagnosis.
However, rights groups have argued that "people should be told when their medical diagnosis comes from AI and not a human doctor." And using the same logic, one could propose that the same warning be issued if, for example, advertising or political speech is AI-generated.
Coming back to Klara And The Sun, Henry Capaldi, a scientist and artist in the book, says to Klara that "there's growing and widespread concern about AF right now People are afraid what's going on inside",meaning inside the "black box" of AI.
Capaldi then goes on to outline the source of the anxieties that wider society has about the decision-making processes of AI.
These anxieties can be summarised as follows: a lack of transparency, how decisions are made inside the black boxand the rules that are used to make a decision.
For example, if a company is using AI to judge an applicant's creditworthiness, the rules that the algorithm uses to make the decision might give rise to some discomfort.
If an applicant is denied a loan for a small business, one could ask, "Was this a fair decision?"
Similarly, if the government uses AI software in criminal justice and allocating public services like income support, there again is a need for accountability, transparency and public confidence in the process.
There is some good news on this front. There is a proposal going around that all machine-learning research papers should include a section on societal harms, as well as the provenance of their data sets.
Some other areas where regulatory oversight may be needed are: the use of AI by politicians to influence voters and marketing companies who create promotions to persuade people to buy their products.
"Government is already undermined when politicians resort to compelling but dishonest arguments. It could be worse still if victory at the polls is influenced by who has the best algorithm,"an editorial last month in the science journal Nature said.
"With artificial intelligence starting to take part in debates with humans, more oversight is needed to avoid manipulation and harm."
Another idea is that in addition to meeting transparency standards, AI algorithms could be required to undergo trials, akin to those required for new drugs, before they can be approved for public use.
Read more:
Artificial intelligence and privacy rights: Daily Star columnist - The Straits Times
Posted in Artificial Intelligence
Comments Off on Artificial intelligence and privacy rights: Daily Star columnist – The Straits Times
What we need to know about artificial intelligence and privacy rights – The Daily Star
Posted: at 5:07 am
Nobel Prize-winning author Kazuo Ishiguro's latest novel Klara and the Sun, his first since receiving the award in literature in 2017, has some relevance for policymakers and ordinary citizens across the globe. The main protagonist in this dystopian science fiction story is Klara, an artificial friend (AF)a human-like teenager who behaves and thinks almost like her cohort of the same age and is a fast learner, as any device or robot using artificial intelligence (AI) can be expected to be. However, what we also learn is that if robots, even if they are super-intelligent, are allowed to make decisions that affect the lives of humans, it might lead to unintended consequences unless there are strict guidelines protecting privacy and other individual rights.
Many discerning readers might already be aware that AI is whipping up quite a storm, particularly as it makes inroads into facial recognition software, law enforcement, and hiring decisions in the corporate world. Policymakers in many countries are alarmed, realising the pros as well as the cons of this revolutionary technology. The European Union (EU), which has been at the forefront of safeguarding privacy rights, unveiled strict regulations in April 2021 to govern the use of AI, a first-of-its-kind policy that outlines how companies and governments can use AI technology, also known as "machine learning". While these new rules are yet to be implemented and are still on the drawing boards, their impact will be similar to that of the General Data Protection Regulation (GDPR), which was drawn up to keep global technology companies such as Amazon, Google, Facebook and Microsoft in check.
The EU has been the world's most aggressive watchdog of the technology industry, with its policies often used as blueprints by other nations. As mentioned, the bloc has already enacted the world's most far-reaching data privacy regulation, the GDPR, and is debating additional antitrust and content-moderation laws. "We have to be aware that GDPR is not made for blockchain, facial or voice recognition, text and data mining [...] artificial intelligence," said Axel Voss, a German member of the European Parliament and one of the creators of GDPR.
AI, in simple terms, is a computer programme that enables the machine to learn how to mimic the problem-solving and decision-making capabilities of the human mind. An AI-enabled device learns how to respond to certain situations and uses algorithms and historical data to recognise a face, predict the weather, or support a search engine like Google. AI is playing a critical role in autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art, playing games (such as Chess or Go), search engines, online assistants (such as Siri), image recognition in photographs, spam filtering, predicting flight delays, and much more.
Large technology companies have poured billions of dollars into developing AI, as also have scores of others that use it to develop medicine, underwrite insurance policies, and judge creditworthiness. Governments use versions of AI in criminal justice and in allocating public services like income support. The potential for AI is enormous, and here is the rub. To what extent can machines be manipulated to gain financial or strategic advantage by those who fund this research or manufacture them? Are they really neutral? Can machines adapt to the humans it interacts with, or do existing biases become hard-wired?
Facial recognition algorithms have been at the centre of privacy and ethics debates. Imagine a scenario where a government buys facial recognition software and uses it to track attendees during protest marches. In Hong Kong, the police used a system, created by Cellebrite of Israel, to access the phones of 4,000 protesters. A researcher at an AI global conference claimed to be able to generate facesincluding aspects of a person's age, gender and ethnicitybased on voices.
Digital rights groups across the US, UK and EU have already raised many issues prompted by advances in AI research, and these include privacy violations, ethical concerns, and lack of human control over AI. Ria Kalluri, a machine-learning scientist at Stanford University in California, said, "because training data are drawn from human output, AI systems can end up mimicking and repeating human biases, such as racism and sexism." Kalluri urged her colleagues to dedicate more efforts into tackling scientific questions that make algorithms more transparent and create ways for non-experts to challenge a model's inner workings.
This controversy brings to the fore the role humans play in training the machines. We each have our biases and preferences, and the machines may inherit them. There is increasing support to "debias the algorithms". "Algorithms exclude older workers, trans people, immigrants, children," said Abeba Birhane, a cognitive scientist at the University College Dublin, citing uses of AI in hiring and surveillance. AI had already evoked criticisms from the late Prof Stephen Hawking, one of Britain's pre-eminent scientists, and Elon Musk, the pioneering entrepreneur, has also raised a red flag.
Having said that, it cannot be gainsaid that AI revolution is here and has come to stay. The important question is, how do we harness the power of AI and manage its negative influence? On the positive side, research has conclusively proven that AI is at least as good as humans in determining medical diagnosis. However, rights groups have argued that "people should be told when their medical diagnosis comes from AI and not a human doctor." And using the same logic, one could propose that the same warning be issued if, for example, advertising or political speech is AI-generated.
Coming back to Klara and the Sun, Henry Capaldi, a scientist and artist, says to Klara, "there's growing and widespread concern about AF (artificial friends) right now People are afraid what's going on inside," meaning inside the "black box" of AI. Capaldi then goes on to outline the source of the anxieties that wider society has about the decision-making processes of AI. These anxieties can be summarised as follows: a lack of transparency, how decisions are made inside the black box, and the rules that are used to make a decision. For example, if a company is using AI to judge an applicant's creditworthiness, the rules that the algorithm uses to make the decision might give rise to some discomfort. If an applicant is denied a loan for a small business, one could ask, "Was this a fair decision?" Similarly, if the government uses AI software in criminal justice and allocating public services like income support, there again is a need for accountability, transparency, and public confidence in the process.
There is some good news on this front. There is a proposal going around that all machine-learning research papers should include a section on societal harms, as well as the provenance of their data sets. Some other areas where regulatory oversight may be needed are: the use of AI by politicians to influence voters and marketing companies who create promotions to persuade people to buy their products. "Government is already undermined when politicians resort to compelling but dishonest arguments. It could be worse still if victory at the polls is influenced by who has the best algorithm," according to an editorial in April in the prestigious journal Nature. "With artificial intelligence starting to take part in debates with humans, more oversight is needed to avoid manipulation and harm." Another idea is that in addition to meeting transparency standards, AI algorithms could be required to undergo trials, akin to those required for new drugs, before they can be approved for public use.
Dr Abdullah Shibli is an economist, currently serving as a Senior Research Fellow at the International Sustainable Development Institute (ISDI), a think-tank based in Boston, USA.
Continue reading here:
What we need to know about artificial intelligence and privacy rights - The Daily Star
Posted in Artificial Intelligence
Comments Off on What we need to know about artificial intelligence and privacy rights – The Daily Star
Can Artificial Intelligence Help Local News? Sure. And It Can Cause Great Harm As Well. – wgbh.org
Posted: at 5:07 am
Ill admit that I was more than a little skeptical when the Knight Foundation announced last week that it would award $3 million in grants to help local news organizations use artificial intelligence. My first reaction was that dousing the cash with gasoline and tossing a match would be just as effective.
But then I started thinking about how AI has enhanced my own work as a journalist. For instance, just a few years ago I had two unappetizing choices after I recorded an interview: transcribing it myself or sending it out to an actual human being to do the work at considerable expense. Now I use an automated system, based on AI, that does a decent job at a fraction of the cost.
Or consider Google, whose search engine makes use of AI. At one time, Id have to travel to Beacon Hill if I wanted to look up state and local campaign finance records and then pore through them by hand, taking notes or making photocopies as long as the quarters held out. These days I can search for Massachusetts campaign finance reports and have what I need in a few seconds.
Given that local journalism is in crisis, whats not to like about the idea of helping community news organizations develop the tools they need to automate more of what they do?
Well, a few things, in fact.
Foremost among the downsides is the use of AI to produce robot-written news stories. Such a system has been in use at The Washington Post for several years to produce reports about high school football. Input a box score and out comes a story that looks more or less like an actual person wrote it. Some news organizations are doing the same with financial data. It sounds innocuous enough given that much of this work would probably go undone if it couldnt be automated. But lets curb our enthusiasm.
Patrick White, a journalism professor at the University of Quebec in Montreal, sounded this unrealistically hopeful note in a piece for The Conversation about a year ago: Artificial intelligence is not there to replace journalists or eliminate jobs. According to one estimate cited by White, AI would have only a minimal effect on newsroom employment and would reorient editors and journalists towards value-added content: long-form journalism, feature interviews, analysis, data-driven journalism and investigative journalism.
Uh, Professor White, let me introduce you to the two most bottom line-obsessed newspaper publishers in the United States Alden Global Capital and Gannett. If they could, theyd unleash the algorithms to cover everything up to and including city council meetings, mayoral speeches and development proposals. And if they could figure out how to program the robots to write human-interest stories and investigative reports, well, theyd do that too.
Another danger AI poses is that it can track scrolling and clicking patterns to personalize a news report. Over time, for instance, your Boston Globe would look different from mine. Remember the Daily Me, an early experiment in individualized news popularized by MIT Media Lab founder Nicholas Negroponte? That didnt quite come to pass. But its becoming increasingly feasible, and it represents one more step away from a common culture and a common set of facts, potentially adding another layer to the polarization thats tearing us apart.
Personalization of news ... puts the public record at risk, according to a report published in 2017 by Columbias Tow Center for Digital Journalism. When everyone sees a different version of a story, there is no authoritative version to cite. The internet has also made it possible to remove content from the web, which may not be archived anywhere. There is no guarantee that what you see will be what everyone sees or that it will be there in the future.
Of course, AI has also made journalism better and not just for transcribing interviews or Googling public records. As the Tow Center report also points out, AI makes it possible for investigative reporters to sift through thousands of records to find patterns, instances of wrongdoing or trends.
The Knight Foundation, in its press release announcing the grant, held out the promise that AI could reduce costs on the business side of news organizations a crucial goal given how financially strapped most of them are. The $3 million will go to The Associated Press, Columbia University, the NYC Media Lab and the Partnership on AI. Under the terms of the grant, the four organizations will work together on projects such as training local journalists, developing revenue strategies and studying the ethical use of AI. It all sounds eminently worthy.
But there are always unintended consequences. The highly skilled people whom I used to pay to transcribe my interviews no longer have those jobs. High school students who might have gotten an opportunity to write up the exploits of their sports teams for a few bucks have been deprived of a chance at an early connection with news an experience that might have turned them into paying customers or even journalists when they got older.
And local news, much of which is already produced at distant outposts, some of them overseas, is about to become that much more impersonal and removed from the communities they serve.
GBH News contributor Dan Kennedys blog, Media Nation, is online at dankennedy.net.
Read the original post:
Can Artificial Intelligence Help Local News? Sure. And It Can Cause Great Harm As Well. - wgbh.org
Posted in Artificial Intelligence
Comments Off on Can Artificial Intelligence Help Local News? Sure. And It Can Cause Great Harm As Well. – wgbh.org
Can artificial intelligence save the British model of education? – The National
Posted: at 5:07 am
Priya Lakhani, a successful entrepreneur who was giving something back to the developing world, has found a cause much closer to home.
The trained barrister and foodstuffs magnate from London has taken up the cause of artificial intelligence in education, hoping that innovation can help British schools that are falling behind their international counterparts.
For more than a decade, Ms Lakhani used a portion of the profits from her first business, a successful brand of Indian cooking sauces, Masala Masala, to fund schools, as well as vaccinations and hot meals, in India.
But struck by the underachievement rates in schools in the UK, she added a focus on her home country.
I just thought, why am I funding schools in Commonwealth countries that are all replicated on the British model, if the British model just doesn't work? she told The National.
In 2009, the year she first looked to the UK situation, a study conducted by Sheffield University found that a fifth of teenagers in England did not have maths and literacy skills good enough to be able to deal with everyday life challenges.
Three years later results of the 2012 Pisa tests, run by the Organisation for Economic Co-operation and Development, placed the UK in the bottom two thirds in literacy and numeracy on the international rankings table and sparked debate about the needs of the national education system.
In the 12 years since, more money and policies have not made much of a dent in the status quo. Only 65 per cent of primary school pupils in the UK in 2019 achieved the governments expected standard in reading, writing and maths.
Ask any parent, teacher or child and they are likely to support these statistics with personal accounts of a stifling, cumbersome and overloaded system that often fails children.
A leading UK educationalist, Sir Anthony Seldon, has written that teachers in the country are overwhelmed by the administrative demands of classrooms that are too big.
It is an "inherently flawed" model that, he argues, artificial intelligence can help upend. There is no more important issue facing education, or humanity at large, than the fast approaching revolution of AI, he writes in his latest book, The Fourth Education Revolution.
Ms Lakhani is a founder of Century Tech, an AI education technology company developed by a team of teachers, neuroscientists and technologists.
It offers a diagnostics and learning tool that promises to help teach students while reducing teachers' workloads.
The AI-powered system constantly adapts and learns to provide personalised learning experiences to every student. It learns how your brain learns, Ms Lakhani told The National.
Founded in 2013, the platform has been developed by teachers, engineers, data scientists, neuroscientists and psychologists.
Feeling strongly that she needed to "solve the problem", Ms Lakhani went round schools in England and found the same problems Mr Seldon discusses in his book.
The one-size-fits-all delivery of education and the time spent by teachers marking, instead of teaching, was failing the system.
You're asking every teacher to be a data analyst, because they've got to figure out very quickly, which student is where, when you make an intervention. If they didn't do that, in an instant, you go through the curriculum, the gaps widen, Ms Lakhani said.
Teaching methods, she said, evolved from a "blackboard to an interactive whiteboard" without really taking advantage of what technology has to offer.
There was more tech on my phone than in the schools. How is this possible? Has anyone actually looked at this? Ms Lakhani said.
After a crash-course in AI and data-based neuroscience she came up with the idea to build a machine that could host any curriculum in any language and that would track students mouse movements to learn, create predictive patterns and then develop a recommended programme of learning.
Then we could create an artificially intelligent machine that learns by itself and gets smarter every second and can personalise it, thereby removing the one size fits all, she told The National.
Century Tech has one million students using its platform in 40 countries. From Eton in England to the Jumeirah English Speaking School in Dubai and state schools in Lebanon teaching Syrian refugees, a wide range of schools have adopted Century Tech in their schools.
It is not a platform just for fee-paying private schools and Ms Lakhani said about 70 per cent of the schools signed up to her platform in the UK are state schools.
Ms Lakhani said many of Century Techs fastest adopters were in the Middle East, where eight countries use it.
If you want to get some traction and you want to work with some of the brightest and the best, and to innovate with them, then actually the Middle East is a perfect place to be, said Ms Lakhani, who counts MiSK and DAS in Saudi Arabia as clients.
As well as growing her business, quicker and bigger sign-ups also help her platform, and its users, to improve.
Because entrepreneurs that are building innovative products and services want to iterate, they want to be agile, they want to get your feedback, they want to act on it. But if it takes so long to adopt something, then you lose that agility, Ms Lakhani, who was awarded an OBE in 2014, told The National.
An analysis done in conjunction with UCL of students using Century Tech found that on average, students' understanding of a topic increased by 30 per cent between their first and second attempts on the platform. Teachers reported back to Ms Lakhanis team a saving of six to seven hours a week normally spent on admin.
At a cost of 50 to 60 pence per month (70 to 84 US cents) per student, the scalability and wide-reach of their platform looks promising. With worldwide school closures for much of the past year and the shock move to digital distant learning, a glaring spotlight is now shining on the future of education.
More than 600,000 children globally were not achieving the minimum proficiency levels in reading and maths before Covid-19, but with 1.6 billion children out of school at the peak of the pandemic, this number is set to increase.
Adopting AI in education is progressively seen as the way to close the gaps and to boost employment-ready skills.
Just last month Jisc, the UKs not-for-profit organisation providing digital services and solutions in education, launched a new National Centre for Artificial Intelligence in Tertiary Education.
The initiative which has been welcomed by global technology companies including Amazon Web Services, Google and Microsoft aims to deliver AI solutions to 60 colleges and 30 universities within five years.
As well as providing examples of AI in education, including students use of chatbots and digital assistants, a report published by the National Centre pointed to the $3.67bn invested in AI Edtech start-ups in 2019 as a strong economic argument for adoption.
AI education solutions are attracting this investment because they offer considerable benefits to learners, teachers, and education institutions, the report said.
You've got schools that may not have considered using the technology and were forced to because of the pandemic
Ms Lakhani said her company raised 15 million ($21.19m) in funding, the last round of which she said was over-subscribed.
Policymakers have been heralding AI increasing reach into everyday life.
In March this year, the government announced the formulation of an AI Strategy to report to digital secretary, Oliver Dowden. The AI Council, an independent expert government advisory committee of which Ms Lakhani is a member, put forward many of the recommendations. She was recently appointed as a non-executive board member of the governments Digital, Culture, Media and Sport department.
Ms Lakhani thinks the pandemic will accelerate AIs adoption in education. You've got schools that may not have considered using the technology and were forced to because of the pandemic, she said.
Having co-founded the Institute for Ethical AI in Education with Mr Seldon and Prof Rose Luckin, she knows full well the need to put a moral compass on the direction of AI in education.
Ms Lakhani looks to a recent encounter with a schoolgirl for inspiration.
During an observation session of students in England using the Century Tech platform, a schoolgirl told Ms Priya that she used to struggle with mathematics and had always been too afraid to raise her hand in class.
Century Tech, she told her, got her to love maths again and to learn better. It also alerted the teacher when she needed help, making the girls shyness no longer a hindrance.
I just think that's worth 15 million. That girl now feels confident in maths, she feels she can do it. She feels like she gets the help that she needs.
Read more from the original source:
Can artificial intelligence save the British model of education? - The National
Posted in Artificial Intelligence
Comments Off on Can artificial intelligence save the British model of education? – The National