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Can common business sense be programmed into AI? Many are certainly trying to do just that. But there are decisions that often require a level of empathy -- let alone common-sense -- that may be too difficult to embed into algorithms. In addition, while AI and machine learning are the hot tickets of the moment, technologists and decision-makers need to think about whether it offers a practical solution to every problem or opportunity.

AI and the Future of Business

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of them.

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These points came up at a panel at the recentAI Summit, in which participants agreed that AI shouldn't be considered the default solution to every business situation that arises. (I co-chaired the conference and moderated the panel.) For starters, AI is still a relatively immature technology, saidDrew Scarano, a panelist at the session and vice president of global financial services atAntWorks. "We might be too reliant on this technology, forgetting about the humans in the loop and how they play an integral part in complementing artificial intelligence in order to get desired results."

AI is being used for many purposes across all industries, but the risk is in de-humanizing the interpersonal qualities that help build and sustain companies. "Today we can use AI for anything from approving a credit card to approving a mortgage to approving any kind of lending vehicle," said Scarano. "But without human intervention to be able to understand there's more to a human than a credit score, there's more to a person than getting approved or denied for a mortgage."

Scarano poo-poos the notion that AI systems comprise anything close to a "digital workforce," noting that "it's just a way to sell more stuff. I can sell 50 digital workers rather than one system. But digital workforce is just a bunch of code that does a specific task, and that task can be repeatable, or be customized." Another panelist,Rod Butters, chief technology officer forAible, agrees, noting that "at the end of the day, it's a machine. In the end, it's all 1s and 0s." The way to make AI more in tune with the business "is to get better tooling, craft, and experience with applying these machines in ways that first and foremost is transparent, and secondly understandable in some way, and ultimately something that is achieving an outcome that is business oriented or community oriented."

AI may be able to deliver fine-grained results based on logic beyond the capacity of human brains, but this may actually "run counter to what the business needs to be doing strategically," says Butters. "Because you can't have the visibility, you get unintended consequences, which can lead to complete disparities and equity in the application of processes to your customer base." Importantly, "there needs to be a feedback loop to ensure solutions you're implementing are resonating with your customers, and they're enjoying the experience as much as you're enjoying creating the experience," according to panelistRobert Magno, solutions architect withRun:AI.

Other experts across the industry also voice concern that AI is being pushed too hard in ways in may not be needed. "AI is not the solution to every business problem," says Pieter Buteneers, director of engineering in machine learning and AI at Sinch. "It sounds sexy, but there are going to be times when it's better to lean into how to best address customer needs rather than blindly investing in new technology."

While AI has the potential to make business processes more efficient and affordable, "at the end of the day, it is still a machine," Buteneers says. "AI lacks human emotion and common sense, so it can make certain mistakes that humans, instinctively, would not. AI can be easily fooled in certain ways that humans would spot from a mile away. For those who worry that AI will replace human jobs, we invariably need people working alongside AI bots to keep them in check and maintain a human touch in business."

AI initiatives "must be aligned with the company's operational needs and workflows to ensure a high level of adoption," agrees Sameer Khanna, senior vice president of engineering at Pager. "Identifying real world problems with user feedback is essential. Once the product is rolled out, there must be a continuous effort to engage users, monitor performance and improve solutions over time."

There are areas worth exploring with AI, however. For instance, "AI can reach and even surpass human performance in strictly defined tasks such as image recognition and language understanding," Buteneers says. "Harnessing the power of natural language processing enables AI systems to understand, write and speak languages like humans do. This offers tremendous benefits for businesses -- deploying an NLP-equipped chatbot or voicebot to complement the work of live service agents, for example, frees up those live agents to respond to complicated inquiries that require a more human approach."

Buteneers notes that "breakthroughs in NLP are making an enormous difference in how AI understands input from humans. I've helped design chatbots that can now understand 100+ languages at once, with AI assistants that can search for answers within any given body of text. AI can even make live customer service agents more effective by reading along during a conversation and offering them suggested responses based on previous conversations, customer context or from a larger knowledge base. Different algorithms in the NLP field can identify and analyze a message that may be fraudulent, which can allow organizations to weed out any spam messages before they get sent to consumers. The applications of NLP can provide countless benefits to any business: it can help save time and money, enhance the customer experience, and automate processes."

Still, human oversight is essential to ensuring these solutions serve customers. "Reviewing AI results should be the standard design process of algorithms -- it's ignorant to believe that once you've set up your model, your job is done," Buteneers says.

Khanna relates how his own company's ideas for AI projects "come primarily from collaboration between our data scientists and internal and client business stakeholders." This partnership "generates well-defined and feasible AI projects that are grounded in business realities," he adds. "Our data engineers, data scientists, and machine learning engineers then implement these projects using open-source technologies and proprietary products from cloud providers."

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The never-ending effort to bake common business sense into artificial intelligence - ZDNet

French VFX powerhouse MacGuff, with headquarters in Paris, is using proprietary artificial intelligence tools, in particular Face Engine and Body Engine, in a broad range of VFX projects.

Current projects in the pipeline include Season 2 of Lupin for Netflix, Htel du temps for France Tlvisions, and Christian Carions Une belle course, starring Dany Boon. The studio also used AI tools in ric Rochants political thriller series The Bureau.

Htel du temps is a perfect example of the power of Face Engine since it brings historic figures back to life, such as late actor Jean Gabin and Princess Diana, to be interviewed by hard-hitting French journalist Thierry Ardisson.

MacGuff has an in-house R&D department that has been developing proprietary AI tools by mixing open-source software with proprietary code. The AI developments are being overseen by co-founder and joint director Rodolphe Chabrier and MacGuffs veteran VFX supervisor Martial Vallanchon.

MacGuff recently received a 200,000 euros ($230,000) grant from Frances CNC to expand its AI engine, as part of the CNCs $11.4 million technological modernization scheme launched in 2021, which has provided support for 20 French studios and digital post-production companies.

Our AI tools can make people look younger and older, or even bring people back to life! explains Philippe Sonrier, MacGuffs other co-founder and joint director. We were the first studio to develop these tools in Europe. They deliver new narrative options and the chance to make more complex characters.

Sonrier adds: AI is totally different from the method that we have known for the past 30 years, primarily based on complex and time-consuming synthesis methods [modeling, rigging, motion capture, photoreal rendering]. AI brings elements of reality in effects. Its amazing how it makes the images more natural. For example, you can film the movements of an actor and a dancer and then merge the two. Its going to revolutionize our industry.

MacGuff was founded in Paris in 1986. In mid-2011 it split into two companies. Universal bought the animation department, renamed as Illumination MacGuff, run by Jacques Bled.

Sonrier is also co-president of FranceVFX, the French visual effects vendors association, created in 2017, which represents 12 studios: MacGuff, BUF, Digital District, Mikros Image, Trimaran, Solidanim, The Yard, Autre Chose, Les Androds Associs, Reepost, La Plante Rouge and D-Seed.

FranceVFX is a lobby for VFX interests and also serves as a liaison mechanism between the participating members. It has facilitated joint cooperation on more ambitious VFX projects.

One recent example was Martin Bourboulons historical drama Eiffel, with 560 VFX shots made by Buf, MacGuff and CGEV, for which the overall VFX supervisor was Olivier Cauwet. Major VFX work is also being developed for Bourboulons upcoming The Three Musketeers DArtagnan and The Three Musketeers Milady, a $85 million two-part saga based on Alexandre Dumas masterpiece.

Collaboration on VFX projects between various studios is a new model for France that has been tested successfully in the U.S., Canada and the U.K., explains Sonrier. It permits us to be more secure. If one vendor has a problem with a project, we can help each other out. The position of the VFX supervisor is emerging in France.

MacGuff works on major international projects as well as French films and series. It produced VFX work on Julia Ducournaus 2021 Cannes Palme dOr winner, Titane, including the CGI sequences that created the car baby.

Our culture is inevitably very French, explains Sonrier. We like to be very close to the creative decisions and become involved in each project as soon as possible. Thats part of our DNA. Titane is a good example. Initially the director tried out animatronics solutions but wasnt happy with them. We used CGI to create the car baby. Its something wed previously tried out in 2006 when creating a fetus for the French documentary Lodysse de la Vie by Nils Tavernier.

VFX work is always very risky in both creative and financial terms, says Sonrier. This is particularly true in the French tradition, because of the status of the director as the auteur and supreme decision-maker.

For major international films and series, Sonrier considers that it is easier to lock down the logistics, but sometimes at the cost of becoming more like a factory pipeline. MacGuff has forged a strong relationship with Netflix, which was cemented by its VFX work on its gentleman thief series Lupin. Another major VFX job produced for Netflix was Alexandre Ajas 2021 survival thriller Oxygen, where the VFX work alone was budgeted at over 1 million ($1.14 million).

MacGuff is now working on a major international series, which involves coordination between several VFX studios. It is also working on a major animation project between France, Belgium and Canada, and an ambitious French robot-themed project that will begin lensing in mid-2022.

More international projects are coming to France in the wake of the change introduced in 2020 to Frances Tax Rebate for International Production (TRIP) scheme, which now offers a 40% rebate on all eligible expenses including for live action spends that are not VFX related for international projects whose VFX expenses surpass 2 million ($2.27 million) spent in France.

High-profile projects attracted by this change include Ridley Scotts 14th century period epic The Last Duel, with VFX work done by Mikros Image. Another example is the 16th-century Medici drama Serpent Queen, produced for Starz by Lionsgate Television and 3 Arts Entertainment.

Smaller-scale international projects can apply for other support mechanisms such as the CVS scheme for ambitious visual and sound projects. The CVS scheme was used on the Lithuanian-French production Vesper Seeds, for which the VFX work was shared with Mathematic, Mikros Liege and Excuse My French.

This dystopian pic, set after the collapse of the Earths ecosystem, is the third feature from Lithuanian helmer Kristina Buozyte and French helmer Bruno Samper, who co-directed a short segment for the 2014 American horror anthology ABCs of Death 2.

MacGuff is also producing VFX work for the documentary Corridor of Power, produced by Dror Moreh, having previously worked on other projects produced by him, such as Oscar-nominee The Gatekeepers and The Human Factor, which won the Grand Prix at Fipadoc 2020.

Other recent French productions handled by the studio include Nicolas Girauds Lastronaute, starring Giraud and Mathieu Kassovitz.

MacGuff is a long-time collaborator of French-Argentine helmer Gaspar No and did the VFX work on his latest feature film, Vortex, in terms of stabilization of the frames, rotations, small morphs, retiming and adjustments to the split screen images.

The studio also provides VFX for documentaries, such as La rafle des notables, produced by Victor Roberts 10.7 Productions, based on Anne Sinclairs book about French concentration camps during World War II. It is also working on a docufiction from 10.7 Productions The Last Secrets of Humanity, directed by Jacques Malaterre, about the prehistoric period in China, including VFX work to recreate prehistoric animals, jointly produced by Mikros and MacGuff.

The company is developing VR/AR and immersive projects, primarily commercials, via its subsidiary Small.

Excerpt from:
MacGuffs Philippe Sonrier on How Artificial Intelligence Tools Will Revolutionize the VFX Industry - Variety

Artificial intelligence and drones are useful for transforming Indian policing in 2022

AI can be a powerful tool for law enforcement and help in addressing many types of crimes. It can help law enforcement to optimize their resources in specific areas and at specific times, to cover as much ground as possible with the same or even fewer resources. Drones with sensors, for instance, can also be used to detect illegal movements such as illegal border crossings, human traffickers, and vessels illegally fishing. Location is a powerful piece of information for AI systems. In India too, artificial intelligence tools are increasingly being put to use. The police departments use of technology is not just limited to facial recognition. It has also been using tools for predictive policing such as crime mapping, analytics, and predictive system, a predictive system that analyses data from past and current phone calls to police hotlines to predict the time and nature of criminal activities in hotspots across the city.

When the respondents were asked about the lack of an Indian police force, the majority of them i.e. 45.8% of 251 respondents, voted for relationship between police and the public as the key factor lacking in the Indian police force. Out of the total, 27.1% respondents selected police accountability. 13.5% of the total respondents selected overburdened force and vacancies, while 11.5% think the process involved in investigation of crime is a lacking factor for the Indian police. The remaining 2.1% think its the infrastructure where Indian police lack.

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There are numerous solutions for the Indian police force that can make it better. From the survey, it is observed that 63% of 251 respondents think that limiting the political executives power of superintendence over police forces will be the best solution for the Indian police force. 15.2% responded to the specialized investigating units as the key solution to the Indian police force. 11.6% of the respondents selected the Community policing model while the rest 10.2% selected Outsourcing and redistributing functions as the best solution for the Indian police force.

From the survey, it is found that 56% of the total respondents think that AI cops must be given a chance over the regular police force, 29.2% think that AI cops may be given a chance, while the remaining 14.6% think that AI cops should not be given a chance over the regular police force.

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

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The Future of Indian Policing with Artificial Intelligence in 2022 and Beyond - Analytics Insight

We have accepted the use of artificial intelligence (AI) in complex processes from health care to our daily use of social media often without critical investigation, until it is too late. The use of AI is inescapable in our modern society, and it may perpetuate discrimination without its users being aware of any prejudice. When health-care providers rely on biased technology, there are real and harmful impacts.

This became clear recently when a study showed that pulse oximeters which measure the amount of oxygen in the blood and have been an essential tool for clinical management of COVID-19 are less accurate on people with darker skin than lighter skin. The findings resulted in a sweeping racial bias review now underway, in an attempt to create international standards for testing medical devices.

There are examples in health care, business, government and everyday life where biased algorithms have led to problems, like sexist searches and racist predictions of an offenders likelihood of re-offending.

AI is often assumed to be more objective than humans. In reality, however, AI algorithms make decisions based on human-annotated data, which can be biased and exclusionary. Current research on bias in AI focuses mainly on gender and race. But what about age-related bias can AI be ageist?

In 2021, the World Health Organization released a global report on aging, which called for urgent action to combat ageism because of its widespread impacts on health and well-being.

Ageism is defined as a process of systematic stereotyping of and discrimination against people because they are old. It can be explicit or implicit, and can take the form of negative attitudes, discriminatory activities, or institutional practices.

The pervasiveness of ageism has been brought to the forefront throughout the COVID-19 pandemic. Older adults have been labelled as burdens to societies, and in some jurisdictions, age has been used as the sole criterion for lifesaving treatments.

Digital ageism exists when age-based bias and discrimination are created or supported by technology. A recent report indicates that a digital world of more than 2.5 quintillion bytes of data is produced each day. Yet even though older adults are using technology in greater numbers and benefiting from that use they continue to be the age cohort least likely to have access to a computer and the internet.

Read more: Online arts programming improves quality of life for isolated seniors

Digital ageism can arise when ageist attitudes influence technology design, or when ageism makes it more difficult for older adults to access and enjoy the full benefits of digital technologies.

There are several intertwined cycles of injustice where technological, individual and social biases interact to produce, reinforce and contribute to digital ageism.

Barriers to technological access can exclude older adults from the research, design and development process of digital technologies. Their absence in technology design and development may also be rationalized with the ageist belief that older adults are incapable of using technology. As such, older adults and their perspectives are rarely involved in the development of AI and related policies, funding and support services.

The unique experiences and needs of older adults are overlooked, despite age being a more powerful predictor of technology use than other demographic characteristics including race and gender.

AI is trained by data, and the absence of older adults could reproduce or even amplify the above ageist assumptions in its output. Many AI technologies are focused on a stereotypical image of an older adult in poor health a narrow segment of the population that ignores healthy aging. This creates a negative feedback loop that not only discourages older adults from using AI, but also results in further data loss from these demographics that would improve AI accuracy.

Even when older adults are included in large datasets, they are often grouped according to arbitrary divisions by developers. For example, older adults may be defined as everyone aged 50 and older, despite younger age cohorts being divided into narrower age ranges. As a result, older adults and their needs can become invisible to AI systems.

In this way, AI systems reinforce inequality and magnify societal exclusion for sections of the population, creating a digital underclass primarily made up of older, poor, racialized and marginalized groups.

We must understand the risks and harms associated with age-related biases as more older adults turn to technology.

The first step is for researchers and developers to acknowledge the existence of digital ageism alongside other forms of algorithmic biases, such as racism and sexism. They need to direct efforts towards identifying and measuring it. The next step is to develop safeguards for AI systems to mitigate ageist outcomes.

There is currently very little training, auditing or oversight of AI-driven activities from a regulatory or legal perspective. For instance, Canadas current AI regulatory regime is sorely lacking.

This presents a challenge, but also an opportunity to include ageism alongside other forms of biases and discrimination in need of excision. To combat digital ageism, older adults must be included in a meaningful and collaborative way in designing new technologies.

With bias in AI now recognized as a critical problem in need of urgent action, it is time to consider the experience of digital ageism for older adults, and understand how growing old in an increasingly digital world may reinforce social inequalities, exclusion and marginalization.

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Artificial intelligence can discriminate on the basis of race and gender, and also age - The Conversation CA