Wikipedia defines artificial intelligence as: In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals.

While AI is usually focused on learning, pattern recognition and problem solving, it can be combined with robotics to perform or assist in the performance of surgical tasks. Da Vinci is a leader in combining AI and robotics for surgery, but there are many other well-funded efforts underway worldwide.

We all know the impact robotics has had in industry, with the manufacture of an automobile being a prime example. Many fewer human hours are required to manufacture an automobile with a fully implemented robotic plant than one relying on human labor only. The robots in an automobile manufacturing plant simply perform repetitive tasks as programmed by their human masters, and they do not use AI to learn how to make a better automobile or improve efficiency themselves. That is left to the human mind.

The potentially malevolent side of AI combined with robotics was graphically portrayed in the 1968 Arthur C. Clarke and Stanley Kubrick movie: 2001: A Space Odyssey, in which the HAL 9000 computer with AI took over the spaceship Discovery One on the way to Jupiter, killing one of the crew members and threatening the other in order to preserve itself. In the end, the human intelligence and resourcefulness of the remaining crew member outsmarted the HAL 9000, which demonstrated the human quality of fear as it was disconnected.

In medicine, one of the most familiar applications of AI has been the reading of EKGs in which pattern recognition is critical. Still, a human analysis by a cardiologist skilled in the art nearly always follows the AI readout before a final diagnosis is made and treatment of a cardiac arrythmia initiated. In ophthalmology, the FDA-approved IDx-DR system (IDx Technologies), created in collaboration with the IBM Watson AI computer, can accurately grade the level of diabetic retinopathy with 87% sensitivity and 90% specificity. But it is not good at performing a differential diagnosis, and a skilled physician must confirm that the patient has diabetic retinopathy and not another retinal pathology such as a retinal vein occlusion.

AI combined with home diagnostics including preferential hyperacuity perimetry and OCT is being developed by Notal Vision and promises to allow patients to determine if they need an urgent visit to their doctor for an anti-VEGF injection or can delay another month. AI is good at flagging potentially abnormal findings in a diagnostic test, for example, encouraging the ophthalmologist to rule out keratoconus in a topography. It can also provide a differential diagnosis for any cluster of symptoms, signs or test results.

AI is here to stay in the field of medicine and, in my opinion, will be a virtuous partner to the ophthalmologist. Ophthalmology is highly dependent on images and diagnostic tests that will respond well to pattern recognition. Robotics combined with AI guidance systems are also entering our surgical field. I do not see AI or robotics as a threat to we ophthalmologists and expect both to be constructive partners as we strive to care for an increasing number of patients with an at best stagnant number of ophthalmologists.

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CasinoBeats Malta Digital’s Future of Gaming track will see some of the leading lights of the igaming industry share their ideas about the next major developments in online casino, slots and poker, and how they will impact on both players and operators.

The virtual conference and exhibition takes place on 30 June – 2 July 2020, with the Future of Gaming content staged over the final two days and accompanied by a programme of themed networking events. 

Highlights of the track include the Leaders Panels that will open each day. On Wednesday, a session sponsored by ICS Digital will examine how operators adapted to the COVID-19 crisis and what opportunities emerged during the changed market conditions of recent months. Speakers include Mårten Forste (COO, LeoVegas) Petra Zackrisson (CCDO, Betano Stoiximan), Americo Loureiro (Director, Solverde) and Shelly Suter-Hadad (CEO, Casumo), with William Scott (Director, Warrenside) handling moderator’s duties. 

Thursday’s panel features a group of high-profile executives offering their insights on how to tackle the major challenges facing the gaming industry today and where the best long-term opportunities may lie. It features Pontus Lindwall (CEO & Founder, Betsson), Jesper Karrbrink (Chairman, Green Jade Games), Ariel Reem (CEO, Genesis Global) and Alexander Martin (CEO, SKS365), with Dinos Stranomitis (COO, Alternar) in the moderator’s chair. 

Stewart Darkin, Managing Director of CasinoBeats, said: “The gaming industry is evolving rapidly to keep pace with constantly changing player tastes and technological advances, and it can be difficult to stay up to date with all the latest developments.

“The high-level speakers on the Future of Gaming track will help CasinoBeats Malta Digital delegates to stay one step ahead, by sharing expert insights on the direction of the industry from the perspectives of major operators, games developers, platform suppliers and leading affiliates.” 

Other sessions on Wednesday include the Affiliate Leaders Panel sponsored by Intertops. It will see Fintan Costello (Managing Director, Bonusfinder.com) moderate a panel of Tobias Svensen (CEO, CasinoGrounds), Jonathan Edelshaim (CEO, Natural Intelligence), Hamish Brown (VP Casino, Catena Media) and Marcos Oliveira (Chief Affiliate Officer, Clever Advertising Group) as they examine how the changing regulatory climate will alter the way affiliates operate. 

The growing importance of casino platforms to the industry will be in the spotlight during the Platforms & Aggregators panel. Melvin Ritsema (MD, Royal Panda), Rui Pena (COO & Co-Founder, Darwin Interactive) and Stian Hornsletten, CCO of session sponsor EveryMatrix, will assess what the platforms’ influence on the market means for both games studios and operators. 

Concluding the Future of Gaming content for 1 July is Live Casino: At A Crossroads, which is sponsored by Pragmatic Play. A panel consisting of Jeremy Taylor (MD, Genting Online), Christos Mavridis (Live Casino Mgr, Stoiximan / Betano), Sam Brown (CCO, Hero Gaming) and Stefania Mincu (Head of Casino, Ellmount Interactive) will consider how the sector can develop new game concepts, cross sell to slots players and stay up to date emerging technologies. 

On Thursday, attention switches to Gamification, its future role in the online casino industry and whether it is of real value to operators. The panel features Ross Parkhill (MD, Rhino Entertainment), Andy Braithwaite (CCO, Scatters), Uri Admon (CEO, Captain Up) and David Flynn (CEO, Swintt), with Karolina Pelc (Strategic Advisor, Basic Strategy) chairing the discussion.

The resurgent Online Poker sector is the next part of the gaming ecosystem to face scrutiny, as Manuel Lopes (CEO, Pokio/Qufan Technology), Sergii Romanenko (COO, Pokerok) and Ivonne Montealegre (Event Director, Malta Poker Festival) look at how the game can sustain its popularity and become a profitable long-term proposition for operators. 

Concluding the track is Acquisition & Personalisation, which sees a panel including Assaf Stieglitz (Founder, Odds1x2.com) and Tal Itzhak Ron (Chairman & CEO, Tal Ron, Drihem & Co) outline the next generation of strategies for attracting and then optimising the lifetime value of players. 

The CasinoBeats Malta Digital agenda also includes tracks about Working in Malta, Technology & Innovation, Regulation & Compliance, and Payments. 

Away from the conference rooms, the 3,000 industry delegates will have multiple opportunities to make new contacts. In addition to the schedule of themed networking sessions, attendees can take part in workshops with sector experts, join in group discussions in the virtual networking bar or use the event platform’s chat facility for one-to-one conversations. 

There is also a 40-booth interactive exhibition showcasing the latest products from both leading suppliers and innovative start-ups, along with a programme of product presentations running throughout the event.  

Find full details of CasinoBeats Malta Digital, including information about how to register and the discounts available on company group passes, at the event’s official website. 

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Operators have had to adapt to these changing times, but so too have their affiliates. Some verticals are growing rapidly, while others have temporarily shrunken into a fraction of what they once were. Jonathan Edelshaim, General Manager at Natural Intelligence, joined our Becky Liggero Fontana to discuss how affiliates are managing in these COVID times.

Even with the return of the Bundesliga and South Korean baseball, sports is not the money maker it once was for affiliates. “What we see is certain verticals that are basically dying because there’s zero interest, whether it’s in gaming, like sports betting, lack of events means pretty much, well I’m not going to say zero interest, but much lower interest,” Edelshaim said. “And then there’s some other vertical, some of the FinTech verticals are declining. And then on the other hand he have some stuff that is exploding, that is spiking. We know of the growing interesting for example in the world of poker, online poker that we’ve all experienced lately, and then of course the bingo and casino, but then some other things that people consume more when they’re at home work, like we’ve seen it with the VPN vertical or mail deliveries in specifically that we operate in the U.S.

The way affiliates decide to spend their money has also had to change, as regulators are taking a harder look at some spaces, while others see much better opportunities for the moment. “So I would say it’s obviously becoming a bit more in focus for the companies, for the operators, for the bookies, affiliate marketing as a channel, for various reasons,” he said. “First of some of them need to generate more revenues online because they have to shut down their offline, the land-based facilities. So they have to focus more and more budgets, and generate more revenues online. And then they need to make sure, even more nowadays, that those affiliate marketing, affiliate marketers, are compliant, are working according to all regulations and are not missing out on anything, because the regulators are even more, you know focused and forcing them to do things by the book.”

Thankfully, most affiliates know they need to keep the watchers happy. “They’re self-regulating, even before the regulators approach them,” Edelshaim said. “So I think it’s becoming more in the focus of these companies, they communicate more with their affiliate marketers, with the different channels, with the different companies that they work with. They’re stricter, but they need they need more out of them in all fronts. So in that perspective we’re under more pressure sort of to deliver on all fronts, which is a good thing eventually, like at the end of the day, because the mature ones, the big ones, the good ones will hopefully come out of this stronger. I have better partnerships and stronger communications with the marketing teams on the operator or bookie side. And it will be obviously a bit more challenging on the compliance, on the regulation front, but it needs to happen, it needed to happen anyway.”

Larger affiliates have a lot to lose if they run afoul of the law, but the worry is that smaller affiliates, desperate to make a buck, might make a bold move. “The affiliate industries is huge, you know, and you have big companies with a lot to risk if they’re not compliant, and there are smaller companies that are taking certainly, taking advantage of certain opportunities and situations,” he said. “I think I cannot speak on behalf of the entire industry, but what we’ve seen from the larger companies, that the ones that cannot risk their business just for tiny profits and see certain opportunities, what we’ve seen is a lot of efforts, not all of them volunteer efforts, you know it’s more, it was something that was pushed our way from the operators. It’s something that we must do, we have to be compliant, we have to work with the operators, we cannot put them at risk, because they’re the ones talking and communicating with regulator, and they’re the ones who’re going to get hit.

Finally, we’re all learning from each other the best practices of working from home during these times of pandemic, and Natural Intelligence is taking notes on what they could improve on, even when normality returns. “First of all, we’re over three hundred and fifty guys working from a Tel-Aviv office, you know, and we didn’t have like work from home scheme,” he said. “So and now all of the sudden we had to move everyone to work from home, and it’s been like four, six, eight weeks, and it’s actually working. And if you do it the right way, it’s actually slightly more efficient, if you know what I mean. So I think that’s one thing that we will take out of this, you can actually do it you can make it easier on your on your employees, on your staff, if you do it in the right way it’s actually more efficient. And number two is, I think we needed like to react, we need to move very quickly and become very creative, especially with the verticals or the companies they are dealing with sports betting. But not only, so we had like close communication with the partners, plus a lot of creativity within the teams, and we’ll need to find ways to preserve that, to figure out how we how we keep that spirit and not going back to just doing sort of more of the same.”

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In this era of artificial intelligence, it’s ironic that there’s so much that we don’t know about natural intelligence. But details of a missing chapter in the story of the brain are about to emerge from a new multi-million pound laboratory that will use wireless and wearable technologies to get inside the heads of toddlers.

The Wohl Wolfson ToddlerLab, part of Birkbeck University’s Centre for Brain and Cognitive Development (CBCD), is due to open in London’s Torrington Square in June. Inside, scientists will be able to scan the brains, monitor the gaze, and chart the hormone levels of one- to three-year-olds as they play in a series of real and virtual environments.

ToddlerLab will be a “world first,” says Denis Mareschal, director of the Centre, who has been working on the project for four years. “There is a black hole in our understanding of the development of toddler’s brains.”

It’s a successor to Birkbeck’s BabyLab, which has led the way in studying brain development since the CBCD opened in 1998. It revealed how babies can learn how the world works from surprising events, linking cause and effect. Researchers use eye tracking to explore what babies are thinking about, and demonstrate how they can figure out what mum or dad mean when they say the word “brick” by tracing their gaze to a piece of Lego. Sensor hairnets can register crackles of electrical brain activity as babies play on their parent’s laps, or fathom words in a stream of sounds (to a baby, all languages are foreign).

Among other projects, BabyLab scientists are helping to understand why people with Down’s syndrome do not get Alzheimer’s, studying the effects of screen time on babies as young as six-months, and seeking early signs of behavioural problems such as ADHD.

But toddlers, well, toddle so these methods have had to be adapted to study them in the new purpose-built lab, which abuts a Georgian house. Thanks to almost £40,000 of crowdfunding, £2.1 million from the Maurice Wohl Charitable Foundation and Wolfson Foundation, and £1.2 million from other backers, ToddlerLab will be equipped with wireless, wearable versions of motion trackers, hairnet sensors and functional near-infrared spectroscopy, in which light absorption is used to measure blood flow in the brain.

The lab includes realistic settings – a typical nursery and home – along with the CAVE, an immersive, VR environment that can recreate farm, supermarket or other surroundings. “Toddlers are active, curious and want to explore,” says Mareschal. “The lab will allow them to roam and behave as they would in the normal world.”

The lab enables researchers to see how children react in different circumstances, and – crucially – with other children present. Some disorders only emerge when toddlers interact with their peers. “Having lots of other children around brings out the difficulties these children have in engaging what others are thinking and how to respond,” he says.

A “biosamples collection suite” will take urine and other samples to study hormones such as cortisol, which is linked with anxiety, and oxytocin, which is released during social bonding. And a “nap lab” will monitor the effects of sleep on brain activity and learning.

The team want to use their new suite of tools to track the extraordinary changes in toddlerhood, when fatty sheaths of myelin boost the ability of nerve cells to conduct signals, swelling the brain as a result. The number of synapses grows from 2,500 per neuron to 15,000 by the age of three and major changes occur in the frontal system, which is central for intelligence, problem solving and organisation.

To investigate, ToddlerLab will focus on how toddlers manage multiple goals. His team will study toddlers as they build houses using Lego, watching the emergence of the critical frontal control system and revealing new insights into behaviours that range from “the terrible twos” to being able to speak fluently, solve problems and other core ingredients of intelligence.

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Simply put, Artificial Intelligence (AI) is the level of intelligence exhibited by machines, in comparison to natural intelligence exhibited by human beings and animals. Therefore it is sometimes referred to as Machine Intelligence. When taught, a machine can effectively perceive its environment and take certain actions to better its chances of achieving set goals successfully. How can a machine be taught?

The root of Machine learning involves writing codes or commands using a programming language that the machine understands. These codes help lay out the foundation of the machines’ thinking faculty, such that the machine is programmed to perform certain functions defined in the codes. These machines are also programmed to use their basic codes to generate a continuous sequence of related codes in order to increase their thinking, learning, and problem-solving capabilities when the workload is increased.

Just as cranes are machines designed to lift heavy loads which humans cannot lift, some machines are programmed to think further and solve analytical problems which are cumbersome to the human brain and some software. This machine assistance for thinking and analysis dates way back to the times of the Abacus. Technology has advanced to the point where there is literally no limit to the amount of information/ data that a machine can work with. This brings us to the topic of Big Data.

Big Data, just as the phrase implies, is simply huge or large or broad or complex or a high amount of a specific set of information which can be understood by, and stored in a computer/ machine. Professionally, Big Data is a field that studies various means of extracting, analysing, or dealing with sets of data that are so complex to be handled by traditional data-processing systems. Such an amount of data requires a system designed to stretch its extraction and analysis capability.

The ideal and most effective means of handling Big Data is with AI Our world is already steeped in Big Data. There is a massive amount of data online and offline about any topic you can think of, ranging from people, their routine, their preferences, etc to non-living things, their properties, their uses, etc.

This huge stockpile of data, when properly harnessed, can give valuable insights and business analytics to the sector/ industry where the data set belongs. Thus, artificially intelligent algorithms are written for us to benefit from large and complex data.

How Companies Are Applying Artificial Intelligence and Big Data

We have addressed the meaning of these terminologies, we will dedicate this part of our Artificial Intelligence essay reviewing how applications are benefiting from the synergy between AI algorithm and Big Data analytics, such as:

● Natural language processing, where millions of samples from the human language are recorded and linked to their corresponding computer programming language translations. Thus, computers are programmed and used in helping organizations analyze and process huge amounts of human language data.

● Helping agricultural organisations and corporations broaden their monitoring capability. AI helps farmers to count and monitor their produce through every growth stage till maturity. AI can identify weak points or defects long before they spread to other areas of these huge acres of land. In this case, satellite systems or drones are used by the AI for viewing and extracting the data.

● Banking and securities, for monitoring financial market activities. For instance, the Securities Exchange Commission (SEC) is using network analytics and natural language processing to foil illegal trading activities in financial markets. Trading data analytics are obtained for high-frequency trading, making decision-based trading, risk analysis, and predictive analysis. They are also used for early fraud warning, card fraud detection, archival and analysis of audit trails, reporting enterprise credit, customer data transformation, etc.

● Communication, Media and Entertainment. AI capabilities can be used for collecting, analyzing, and utilizing consumer insights. Leveraging mobile and social media content. Understanding patterns of real-time, media content usage. Companies in this industry can simultaneously analyse their customer data along with customer behavioural data to create detailed customer profiles that will be used for creating content for a diverse target audience, recommending content, and measuring content performance.

● Healthcare providers have benefited from the large pool of health data Prescriptions and health analysis have been simplified by AI. Hospitals are using data collected by millions of cell phones and sensors, allowing doctors to use evidence-based medicine. Also, the spread of chronic diseases is identified and tracked faster.

● In the Educational sector, AI syncs with Big Data analytics for various purposes, such as for tracking and analysing when a student logs into the school’s system, the amount of time spent on the different pages of the system, and the overall progress of students over time. It is also useful for measuring the effectiveness of teachers. Thus, teachers’ performance is analysed and measured with respect to the number of students, various courses, student aspirations, student demographics, behavioural patterns, and many other data.

● In Manufacturing, inventory management, production management, supply chain analysis and customer satisfaction techniques are made seamless. Thus, the quality of products is improved, energy efficiency is ensured, reliability levels rise, and profit margins increase.

● In the Natural Resources sector, the synergy of AI and Big Data makes predictive modelling possible. Allowing for the quick and easy analysis of large graphical data, geospatial data, temporal data, seismic interpretation and reservoir characterization.

● Governments around the world use AI for various applications such as public facial recognition, vehicle recognition for traffic management, population demographics, financial classifications, energy exploration, environmental conservation, infrastructure management, criminal investigations, and much more.

Other areas where AI is used in Big Data are Insurance, Retail & Wholesale Trade, Transportation, and Energy & Utilities.

Final Thoughts

In conclusion, we have been able to confirm that there are huge investments in the use of AI in Big Data analysis for the benefit of all. Data sets will continue to increase, therefore the level of application and investment will continue to increase over time. Human intervention, as always, will continue to be relevant, although this relevance is projected to continue reducing with time.

One can rightly argue that “Artificial Intelligence is useless without data and data is insurmountable without AI ”. Also, both AI and Big Data are literally impossible without human intervention and interaction.

AI system which enables Machine learning solutions is the future of the development of business technologies and processes. Such enabled Machine Learning applications automate data analysis and find new insights that were previously impossible to imagine by processing data manually or with traditional methods. This possibility of increasing the predictability of certain events allows us to completely redraw our approach to how everything is done.

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CasinoBeats Malta Digital is to reflect the crucial role that affiliates continue to play in the online casino industry by making the future of igaming affiliation one of the key themes of the agenda for the three-day virtual conference and exhibition.

The content will feature insights and ideas from some of the leading executives in the sector, while there will also be plenty of networking opportunities for affiliates and operator affiliate managers during the event, which takes place on 30 June – 2 July 2020.

Among the key sessions is the Affiliate Leaders Panel, sponsored by Intertops, which has a speaker line-up that includes Tobias Svensen (CEO, CasinoGrounds), Hamish Brown (VP casino, Catena Media), Jonathan Edelshaim (general manager, Natural Intelligence) and Marcos Oliveira (chief affiliate officer, Clever Advertising Group).

It will examine the challenges facing major igaming affiliates, the ways in which the changing regulatory climate is influencing how affiliates operate, and what opportunities are available to new entrants to the market. 

Another highlight is the Acquisition & Personalisation session, which will see a panel including Assaf Stieglitz (founder, Odds1x2.com) share their experiences of the most effective methods for the slots sector to acquire new players and optimise the lifetime value of customers. Panelists will also outline their thinking on how these techniques may evolve as the market continues to change.  

Delegates can also look forward to some practical advice during the Affiliates: Compliance Minefield session, as a panel that includes Ian Sims (founder, Rightlander) details how  igaming affiliates can stay simultaneously onside with advertising guidelines, operator policy and regulatory requirements. 

In addition to the marketing-focused sessions, there will be panels on other topics of interest to affiliates, such as developments in the Japanese and Swedish markets, and the long-term outlook for live casino, online poker and bingo.   

Away from the conference rooms, operator affiliate managers and delegates from affiliates will have lots of opportunities to connect during CasinoBeats Malta Digital. The event has a virtual networking lounge, a virtual bar and one-to-one chat functionality, along with a selection of themed networking hours designed to bring together stakeholders interested in specific market sectors. The schedule will include a dedicated affiliate session. 

Stewart Darkin, managing director of CasinoBeats, said: “We’ve chosen to make affiliate marketing a central theme for the event in recognition of the fact that igaming affiliates remain an important part of the online casino ecosystem. 

“The strategies affiliates use to achieve results for operators are constantly evolving, and delegates attending the conference sessions will discover plenty of new perspectives on the coming trends and long-term future of the sector. 

“The event will also provide a relaxed setting for operators to connect and talk business with both market-leading super affiliates and innovative new affiliates.” 

CasinoBeats Malta Digital will see 3,000 industry delegates, including more than 1,200 representatives of major casino, slots and poker operators, gather for a five-track conference, interactive exhibition featuring 40 leading suppliers, and selection of virtual networking events. 

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It may not be the kind of open call to artists you would expect in the midst of a health crisis.

But an ambitious project by Eyebeam, the 22-year-old New York-based nonprofit that promotes art on the forefront of technological innovation, is all about tasking artists with imaging new forms of equitable digital engagement.

Through the project, titled Rapid Response a for a Better Digital Future, Eyebeam is asking artists to design “new ways of interacting through the internet,” according to a prompt. Among the proposals that will be considered are those that make the internet more accessible; ones that develop artificial and natural intelligence solutions; and others that help artists develop new and essential skills.

The initiative will unfold in two phases. In the first, the organization will hand out 27 $5,000 grants to artists who apply through the open call, which closes on May 30. In phase two, those artists will be invited to apply for one of five additional $25,000 grants to turn their ideas into reality. 

The initiative came together in March, after Eyebeam was forced to cancel its longstanding residency program, which has more than 500 alumni, including Jill Magid, Cory Arcangel, and Torkwase Dyson.

“I threw my hands in the air and said, ‘I don’t know what a residency means right now. I don’t know what a program that’s predicated on people coming together in space will look like in the future,’” Roderick Schrock, Eyebeam’s executive director, tells Artnet News.

As the organization batted around new initiatives to replace the program, artist Hito Steyerl, who serves as one of the nonprofit’s advisors, observed that many of the suggestions being made had to do with surveillance capitalism, a term coined by theorist Shoshana Zuboff to describe an era in which big data has supplanted oil as the world’s most prized currency.

“That’s the thing that our organization needs to prioritize and turn the heat up on, because it’s foundational to a lot of the inequities and issues that the other suggestions were addressing,” Schrock says.

So Eyebeam put the money earmarked for its residency towards the Rapid Response initiative, and two philanthropic bodies—the Henry Luce Foundation and the Mellon Foundation—chipped in another $300,000, effectively doubling the program’s budget. (The money not going to artists will be put towards a project manager and an independent evaluator to oversee the project, as well as jury and advisor fees.)

The open call went live April 21. Since then, Eyebeam has already received more applications than it ever gets for its residency program—and it expects many more submissions to come in.

“If there was ever a time to create a protected space outside the economies of art and technology,” Schrock says, “this is the moment to do that.”

The post The Nonprofit Eyebeam Is Handing Out Tens of Thousands of Dollars to Artists to Develop New Tools to Fight Digital Inequality appeared first on Artificial Intelligence.

There is clearly a mixture of excitement about a future driven by digital and AI and a desire to better understand what it means and how to prepare for it. Everybody is discerning and working on AI and their digital future. Many executives have come to terms with the idea that disruption is a fact of life and that their companies need to transform.

But what exactly is AI and how can it shape the future of GRC?

Artificial intelligence (AI) deals with building smart machines capable of performing tasks that typically require human intelligence. Patrick Winston, the Ford professor of artificial intelligence and computer science at MIT, defines AI as “algorithms enabled by constraints, exposed by representations that support models targeted at loops that tie thinking, perception and action together.”

According to Wikipedia, AI, sometimes called machine intelligence, is intelligence validated by machines, in contrast to natural intelligence displayed by humans and animals. It is the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.

The term is often used to describe machines (or computers) that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem solving”

Although artificial intelligence educes thoughts of science narrative, studies have shown that it already has many usages today:

• Spam filters on email;

• Personalization: Online services use artificial intelligence to personalize experience. Services, like Amazon or Netflix, “learn” from an individual’s previous purchases and the purchases of other users in order to recommend relevant content;

• Fraud detection: Banks, for instance, use artificial intelligence to determine if there is strange activity on an account. Unexpected activity, such as foreign transactions, could be flagged by the algorithm;

• Smart assistants (like Siri and Alexa);

• Disease mapping and prediction tools;

• Manufacturing and drone robots;

• Optimized, personalized healthcare treatment recommendations;

• Conversational bots for marketing and customer service;

• Robo-advisors for stock trading;

• Social media monitoring tools for dangerous content or false news; and

• Song or TV show recommendations from Spotify and Netflix.

Hardly a day passes without a news story about a high-profile data breach or a cyber-attack costing millions and millions of dollars in damages. Cyber losses are difficult to approximate, but the International Monetary Fund [IMF] places them in the range of US$100–$250 billion annually for the global financial services industry.

Furthermore, with the ever-growing pervasiveness of computers, mobile devices, servers and smart devices, the cumulative threat exposure grows each day.

While the business and policy groups are still beleaguered to shawl their heads around the cyber realm’s brand-new importance, the use of AI to cyber security is foreshowing even greater changes.

One of the fundamental purposes of AI is to automate tasks that heretofore would have required human intelligence. Cutting down on the labor resources an organization must employ to complete a project, or the time an individual must devote to routine tasks, enables terrific gains in efficiency.

The nature of risks is unremittingly fluctuating and evolving at unprecedented levels and hence implementing a successful risk management program is the call for organizations looking to safeguard their hard-earned reputation. Failure to do so could be injurious, as many organizations in the past have realized the hard way.

The standard organizational framework used to manage risk and compliance are the three [3] lines of defense:

• The first line of defence (functions that own and manage risks);

• The second line of defence (functions that oversee or who specialise in compliance or the management of risk); and

• The third line of defence (functions that provide independent assurance).

A key requirement of the lines of defense is the assistance provided to various levels of management. While first and second lines of defense are archetypally organized to support levels of management, the 3rd line of defense classically works with management and the board to surface risks and compliance issues and works to address slits and deficiencies.

In order to provide proper assistance for these levels of management, the lines of defense need to provide insights that enable:

• Enriched execution on a daily basis of the performance of risk and control activities;

• Finer and tenacious control and management of the activities, and

• Forward and outward looking comprehensions for strategic risk management.

Integrated GRC platform is the only solution to help businesses manage risks across the organization while driving overall enterprise performance and being flexible enough to keep pace with a rapidly-changing environment.

As these platforms allow companies to meet their GRC targets by automating the workflow, many organizations are espousing GRC platforms to augment their operational activities.

In this day and age of disruption, technology is a sturdy enabler of business. And arguably, few developments in technology have generated as much interest as AI. From digital assistants to streaming services, AI is ubiquitous, with seemingly endless possibilities. But beyond all the flimflam, what are the practical applications of AI in GRC?

Artificial Intelligence (AI) in GRC is the need of the hour. As companies expand their digital footprints, cyber security vulnerabilities increase due to huge amount of data being produced. Surely, the demand for intelligent use of accumulated risk data will only increase.

GRC solutions that incorporate AI and its application Machine Learning (ML), will play a key role. The key players in GRC industry are working hard to offer AI-as-a-Service (AlaaS), particularly to industries where data is too valuable.

A recent report  found that the use of artificial intelligence will bring about massive changes to GRC. By automating payments, calculating risk, and maintaining records, the study broke down how the technology will influence each role within GRC:

• Risk manager –With the rise of AI, risk managers’ tasks will fundamentally shift to data-based identification and interpretation of changes in risk exposures. This includes the ability to assess trends by exploring existing facts and applying cognitive skills to understand the analyses of large volumes of data;

• Compliance manager –With automated reports, the future responsibility of compliance managers goes one step further: identifying internal or external dangers as well as the management of cybercrime. This will require the ability to work adroitly and to solve problems independently;

• Fraud examiner – The role of the fraud examiner will shift intensely as artificial intelligence becomes more ubiquitous. The main tasks will move from reviewing reports to performing fraud assessments and developing KRIs for avoiding future cases of fraud;

• Auditor – The role of the auditor may not change markedly; and

• Treasury manager –With AI, the treasury manager must build up new expertise to be able to utilize technology to monitor liquidity and risk management, to monitor and optimize cash-flow streams, and to give recommendations to the executive board with regard to strategy development.

While many fear that the widespread use of automation will displace white-collar jobs, AI is far more likely to be used as an augmentation tool.

Overall, productivity will improve and fast-track implementation of elementary financial tasks. It will also impact almost every role within finance and GRC, and rather than hiding behind fear, should motivate everyone to further develop their methodological skills to keep pace with transformation.

The post Leveraging artificial intelligence to energize grc in a disruptive world appeared first on Artificial Intelligence.

There is clearly a mixture of excitement about a future driven by digital and AI and a desire to better understand what it means and how to prepare for it. Everybody is discerning and working on AI and their digital future. Many executives have come to terms with the idea that disruption is a fact of life and that their companies need to transform.

But what exactly is AI and how can it shape the future of GRC?

Artificial intelligence (AI) deals with building smart machines capable of performing tasks that typically require human intelligence. Patrick Winston, the Ford professor of artificial intelligence and computer science at MIT, defines AI as “algorithms enabled by constraints, exposed by representations that support models targeted at loops that tie thinking, perception and action together.”

According to Wikipedia, AI, sometimes called machine intelligence, is intelligence validated by machines, in contrast to natural intelligence displayed by humans and animals. It is the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.

The term is often used to describe machines (or computers) that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem solving”

Although artificial intelligence educes thoughts of science narrative, studies have shown that it already has many usages today:

• Spam filters on email;

• Personalization: Online services use artificial intelligence to personalize experience. Services, like Amazon or Netflix, “learn” from an individual’s previous purchases and the purchases of other users in order to recommend relevant content;

• Fraud detection: Banks, for instance, use artificial intelligence to determine if there is strange activity on an account. Unexpected activity, such as foreign transactions, could be flagged by the algorithm;

• Smart assistants (like Siri and Alexa);

• Disease mapping and prediction tools;

• Manufacturing and drone robots;

• Optimized, personalized healthcare treatment recommendations;

• Conversational bots for marketing and customer service;

• Robo-advisors for stock trading;

• Social media monitoring tools for dangerous content or false news; and

• Song or TV show recommendations from Spotify and Netflix.

Hardly a day passes without a news story about a high-profile data breach or a cyber-attack costing millions and millions of dollars in damages. Cyber losses are difficult to approximate, but the International Monetary Fund [IMF] places them in the range of US$100–$250 billion annually for the global financial services industry.

Furthermore, with the ever-growing pervasiveness of computers, mobile devices, servers and smart devices, the cumulative threat exposure grows each day.

While the business and policy groups are still beleaguered to shawl their heads around the cyber realm’s brand-new importance, the use of AI to cyber security is foreshowing even greater changes.

One of the fundamental purposes of AI is to automate tasks that heretofore would have required human intelligence. Cutting down on the labor resources an organization must employ to complete a project, or the time an individual must devote to routine tasks, enables terrific gains in efficiency.

The nature of risks is unremittingly fluctuating and evolving at unprecedented levels and hence implementing a successful risk management program is the call for organizations looking to safeguard their hard-earned reputation. Failure to do so could be injurious, as many organizations in the past have realized the hard way.

The standard organizational framework used to manage risk and compliance are the three [3] lines of defense:

• The first line of defence (functions that own and manage risks);

• The second line of defence (functions that oversee or who specialise in compliance or the management of risk); and

• The third line of defence (functions that provide independent assurance).

A key requirement of the lines of defense is the assistance provided to various levels of management. While first and second lines of defense are archetypally organized to support levels of management, the 3rd line of defense classically works with management and the board to surface risks and compliance issues and works to address slits and deficiencies.

In order to provide proper assistance for these levels of management, the lines of defense need to provide insights that enable:

• Enriched execution on a daily basis of the performance of risk and control activities;

• Finer and tenacious control and management of the activities, and

• Forward and outward looking comprehensions for strategic risk management.

Integrated GRC platform is the only solution to help businesses manage risks across the organization while driving overall enterprise performance and being flexible enough to keep pace with a rapidly-changing environment.

As these platforms allow companies to meet their GRC targets by automating the workflow, many organizations are espousing GRC platforms to augment their operational activities.

In this day and age of disruption, technology is a sturdy enabler of business. And arguably, few developments in technology have generated as much interest as AI. From digital assistants to streaming services, AI is ubiquitous, with seemingly endless possibilities. But beyond all the flimflam, what are the practical applications of AI in GRC?

Artificial Intelligence (AI) in GRC is the need of the hour. As companies expand their digital footprints, cyber security vulnerabilities increase due to huge amount of data being produced. Surely, the demand for intelligent use of accumulated risk data will only increase.

GRC solutions that incorporate AI and its application Machine Learning (ML), will play a key role. The key players in GRC industry are working hard to offer AI-as-a-Service (AlaaS), particularly to industries where data is too valuable.

A recent report  found that the use of artificial intelligence will bring about massive changes to GRC. By automating payments, calculating risk, and maintaining records, the study broke down how the technology will influence each role within GRC:

• Risk manager –With the rise of AI, risk managers’ tasks will fundamentally shift to data-based identification and interpretation of changes in risk exposures. This includes the ability to assess trends by exploring existing facts and applying cognitive skills to understand the analyses of large volumes of data;

• Compliance manager –With automated reports, the future responsibility of compliance managers goes one step further: identifying internal or external dangers as well as the management of cybercrime. This will require the ability to work adroitly and to solve problems independently;

• Fraud examiner – The role of the fraud examiner will shift intensely as artificial intelligence becomes more ubiquitous. The main tasks will move from reviewing reports to performing fraud assessments and developing KRIs for avoiding future cases of fraud;

• Auditor – The role of the auditor may not change markedly; and

• Treasury manager –With AI, the treasury manager must build up new expertise to be able to utilize technology to monitor liquidity and risk management, to monitor and optimize cash-flow streams, and to give recommendations to the executive board with regard to strategy development.

While many fear that the widespread use of automation will displace white-collar jobs, AI is far more likely to be used as an augmentation tool.

Overall, productivity will improve and fast-track implementation of elementary financial tasks. It will also impact almost every role within finance and GRC, and rather than hiding behind fear, should motivate everyone to further develop their methodological skills to keep pace with transformation.

The post Leveraging artificial intelligence to energize grc in a disruptive world appeared first on Artificial Intelligence.

Every year with the growth in new technologies and inventions there have been an astounding growth in volume of intellectual property literature. Internationally, this data has to be gathered, stored, and classified in multiple formats and languages so that it can be used as and when required. However, data alone does not create a competitive advantage, extracting significant and actionable information from this data deluge represents a major challenge and an opportunity at the same time. Analysing patent documents from the pile of data manually is getting out of question day by day as it demands extensive time and resources. So, the examiners and patent analyst need all available tools at their disposal to perform this tedious task. One of the tools with a tremendous potential is Artificial Intelligence (AI). At its core, artificial intelligence is a computer that has been programmed to mimic the natural intelligence of human beings by learning, reasoning and making decisions.

From the days of fully constructed Boolean searches, search and analytics have evolved, thanks to AI-based semantic search algorithms to provide more efficient and accurate search result than ever before. A major advantage of artificial intelligence is its ability to provide repeated results as these systems are not hindered by inexperience or fatigue. Artificial intelligence tools have potential to significantly streamline and automate the patent search process and the increase the quality and speed of theobtaining results by reducing the amount of time examiners and analyst spend researching, for example,a prior art research project that can runs into days and weeks, can be performed by an AI tool in a matter of hours. Some existing tools, that are really advanced, also incorporate natural language based input that permitsa searcher to include natural language terms that can be comprehended by the backend artificial intelligence engine, which recovers comparable documents available in different languages. 

The European Patent Office (EPO) uses Intelligent machine translation tool “Patent Translate” to allow for translation of patent publications from 32 languages into the EPO official languages of English, French and German. The US patent office (USPTO)uses artificial intelligence to help examiners to review pending patent applications by augmenting classification and searches – currently a high priority – with it. The UK patent office (UKIPO) also uses artificial intelligence solutions for prior art searching. IBM is offering Watson, an IP advisor that leverages artificial intelligence for fast patent ingestion, better insights, and analytics. Turbopatent, a company that develops applications to automate and streamline the patent protection process, has introduced two artificial intelligence products for patent lawyers. Roboreview, a cloud-based product that analyses drafted patent applications and rapid response, a product that assists lawyers in writing responses to office actions.

Many key players in the industry like PatSeer, Questel, have been using artificial intelligence in combination with machine learning & semantic-based algorithms to provide patent analytics tools and software.With the help of these tools and software we can now:

• Search prior art and analyse from a large number of patent families in multiple languages
• Analyse citations, search for assignees, inventors and perform design searches directly 
• Tracing patent office actions or payment of maintenance fees
• Removing un-patentable inventions up front, maintaining and parsing patent portfolios and reducing the patent sample space to search from available pile.

There are some opposing views relating to the implementation and benefit of artificial intelligence tools and techniques – there are people who are concerned about the peculiarities of language used within patent documents, and doubt that how these tools can deal with the inherent ambiguities i.e.its lack of human reasoning as it is unable to carry out a ‘sanity check’ of results or inventions and lacks the experience that leads to a person’s intuitive response to situations.There have been some recorded incidents where the AI based tools failed to perform what it was intended to do.

All in all, it’s difficult to say whether the AI based tools will be able to completely mimic the human beings and perform same level of analysis or whether they will only reach to the extent of an “additional help” to a patent searcher – we will see in coming times. 

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