Collaborating Authors


How Samsung is using AI software to up the camera game on its smartphones


Samsung has applied approximately 60 new AI models run by the neural processing unit (NPU) to optimise the functions of the Galaxy S22 Ultra smartphone camera, a company executive said. This has allowed the South Korean tech giant to offer camera experiences that can satisfy casual users with the best photographs possible and professional users with RAW files equivalent to those taken on DSLR cameras, said Joshua Sungdae Cho, vice president and head of visual software R&D at Samsung's MX Business, in an interview with ZDNet. "We've applied NPUs to our smartphones for the first time three years ago," said Cho. "At the time, these NPU ran approximately 10 AI models. On the Galaxy S22 Ultra, there are now 60 AI models. Basically, the NPU is involved in nearly all functions of the cameras."

The Machine Ethics Podcast: AI Audits with Ryan Carrier


Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. This episode we're chatting with Ryan Carrier about the positivity of the ForHumanity community, being compelled to do something about AI technologies' negative impact, AI audits, and topics including trust, oversight, governance, privacy, cyber security, bias, creating an infrastructure of trust, disclosing found risks and the ethical decisions, the new industry of AI audits, human wellbeing as the whole point of business, and more… Ryan Carrier founded ForHumanity after a 25 year career in finance. His global business experience, risk management expertise and unique perspective on how to manage risk led him to launch the non-profit entity, ForHumanity, personally. Ryan focused on Independent Audit of AI Systems as one means to mitigate the risk associated with artificial intelligence and began to build the business model associated a first-of-its-kind process for auditing corporate AIs, using a globally, open-source, crowd-sourced process to determine "best-practices". Ryan serves as ForHumanity's Executive Director and Chairman of the Board of Directors.

Sustainability starts in the design process, and AI can help

MIT Technology Review

Artificial intelligence helps build physical infrastructure like modular housing, skyscrapers, and factory floors. "…many problems that we wrestle with in all forms of engineering and design are very, very complex problems…those problems are beginning to reach the limits of human capacity," says Mike Haley, the vice president of research at Autodesk. But there's hope with AI capabilities, Haley continues "This is a place where AI and humans come together very nicely because AI can actually take certain very complex problems in the world and recast them." And where "AI and humans come together" is at the start of the process with generative design, which incorporates AI into the design process to explore solutions and ideas that a human alone might not have even considered. "You really want to be able to look at the entire lifecycle of producing something and ask yourself, 'How can I produce this by using the least amount of energy throughout?'" This kind of thinking will reduce the impact of, not just construction, but any sort of product creation on the planet. The symbiotic human-computer relationship behind generative design is necessary to solve those "very complex problems"--including sustainability. "We are not going to have a sustainable society until we learn to build products--from mobile phones to buildings to large pieces of infrastructure--that survive the long-term," Haley notes. The key, he says, is to start in the earliest stages of the design process. "Decisions that affect sustainability happen in the conceptual phase, when you're imagining what you're going to create." He continues, "If you can begin to put features into software, into decision-making systems, early on, they can guide designers toward more sustainable solutions by affecting them at this early stage."

The Machine Ethics Podcast: AI readiness with Tim El-Sheikh


Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. Tim El-Sheikh is a biomedical scientist, entrepreneur, and CEO and co-founder of Nebuli, the world's first Augmented Intelligence Studio. A self-taught coder since the age of 10, he has a real passion for designing and intelligent algorithms. After a master's degree in Computer Science and Information Technology, Tim combined his experience in design, neuroscience, and engineering to start as an entrepreneur in online multitier system architectures in the media and advertising sectors, scientific publishing, and social enterprises. From there, he founded Nebuli, an augmented Intelligence studio that focuses on building dynamic user experiences, solving complex problems and bringing positive impact into people's lives by harnessing the power of ethical AI.

Forward Thinking on China and artificial intelligence with Jeffrey Ding


In this episode of the McKinsey Global Institute's Forward Thinking podcast, host Michael Chui speaks with Jeffrey Ding, researcher and founder of the ChinAI Newsletter, about information asymmetry in artificial intelligence between China and the West. They cover why data may not be like oil, the Chinese industry adage on products, platforms, and standards, "unsexy AI," and more. An edited transcript of this episode follows. Subscribe to the series on Apple Podcasts, Google Podcasts, Spotify, Stitcher, or wherever you get your podcasts. Anna Bernasek, co-host: Michael, there's a lot of talk right now about artificial intelligence, or AI, and what it means for global competition. I'm really glad we've got a guest today that can talk to us about what's really going on, particularly when it comes to the US and China. It definitely is a fascinating topic--at least, I find it personally. I'm a former AI practitioner and more recently, at the McKinsey Global Institute, have been able to study the impact of AI on business and more broadly. And one of the reasons I'm so excited about today's conversation is because it's with somebody you probably don't know yet but probably should. He's famous in certain corners of the internet but his work, it turns out, is relevant everywhere.

Let's Talk About Amazon's Home-Patrolling Robots


About this time every year, Amazon announces a slew of new products. Some of them are fairly normal: new Echo speakers, smart screens, video doorbells. But sometimes the company will roll out something truly bonkers, like a flying home security drone or a Roomba-like robot with an extending periscope camera that wheels around your house. Outlandish or otherwise, the company's output offers a look at where it's headed. And this year, Amazon seems increasingly intent on becoming a home security company.

How to Implement Artificial Intelligence in Marketing: Rajkumar Venkatesan on Marketing Smarts [Podcast]


Artificial intelligence (AI) and machine-learning (ML) have quickly grown beyond a few major tech companies and hardcore academic researchers. Every marketing organization can tap into the power of AI to streamline operations and grow the business. The new book The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing provides a growth framework for business and marketing leaders to implement AI using a five-stage model called the "AI Marketing Canvas." On this episode of Marketing Smarts, I speak with co-author Rajkumar Venkatesan about how he and his co-writer developed those stages by studying leading global brands. We cover examples of brands―including Google, Lyft and Coca-Cola―that have successfully woven AI into their marketing strategies. This is not a conversation about coding for AI models. Raj and I talk about how marketing leaders can go from "zero to hero" with AI in marketing, and what that means for your team and your company culture. Listen to the entire show now from the link above, or download the mp3 and listen at your convenience.

Podcast: Beating the AI hiring machines

MIT Technology Review

When it comes to hiring, it's increasingly becoming an AI's world--we're just working in it. In this, the final episode of Season 2 of our AI podcast "In Machines We Trust" and the conclusion of our series on AI and hiring, we take a look at how AI-based systems are increasingly playing gatekeeper in the hiring process--screening out applicants by the millions, based on little more than what they see in your résumé. In fact, an increasing number of people and services are designed to help you play by--and in some cases bend--their rules to give you an edge. This is NOT Jennifer Strong. To wrap up our hiring series, the two of us took turns doing the same job interview, because she was curious if the automated interviewer would notice. So, human Jennifer beat me as a better match for the job posting, but just by a little bit. It got better personality scores. Because, according to this hiring software, this fake voice is more spontaneous. It also got ranked as more innovative and strategic, while Jennifer is more passionate, and she's better at working with others. Jennifer: Artificial intelligence is increasingly used in the hiring process. And these days algorithms decide whether a resume gets seen by a human, gauge personalities based on how people talk or play video games, and might even interview you. In a world where you no longer prepare for those interviews by putting your best foot forward--what does it mean to present your best digital self? Sot: Youtube clips montage: Vlogger 1: Want to know three easy hacks to significantly improve your performance on video interviews like HireVue, Spark Hire, or VidCruiter? Vlogger 2: Please do make sure you watch this from beginning to end, because I want to help you to pass your interview.

Cybersecurity can protect data. How about elevators?

MIT Technology Review

Advanced cybersecurity capabilities are essential to safeguard software, systems, and data in a new era of cloud, the internet of things, and other smart technologies. In the real estate industry, for example, companies are concerned about the potential for hijacked elevators, as well as compromised building management and heating and cooling systems. According to Greg Belanger, vice president of security technologies at CBRE, the world's largest commercial real estate services and investment company, securing the enterprise has grown more complex--security teams must be familiar with controls and hardware on new devices, as well as what version of firmware is installed and what vulnerabilities are present. For example, if a heating, ventilation, and air-conditioning (HVAC) system is connected to the internet, he questions, "Is the firmware that's running the HVAC system vulnerable to attack? Could you find a way to traverse that network and come in and attack employees of that company?" Understanding enterprise vulnerabilities are crucial to safeguard physical assets but investing in the right tools can also be a challenge, says Belanger. "Artificial intelligence and machine learning need large sets of data to be effective in delivering the insights," he explains. In the era of cloud-first and industrial internet of things, the perimeter is becoming far more fluid. By applying AI and machine learning to data sets, he says, "You start to see patterns of risk and risky behavior start to emerge." Another priority when securing physical assets is to translate insights into metrics that C-suite leaders can understand, to help boost decision-making. CEOs and members of boards of directors, who are becoming more security savvy, can benefit from aggregated scores for attack surface management. "Everybody wants to know, especially after an attack like Colonial Pipeline, could that happen to us? How secure are we?" says Belanger.

Podcast: Want a job? The AI will see you now


In the past, hiring decisions were made by people. Today, some key decisions that lead to whether someone gets a job or not are made by algorithms. The use of AI-based job interviews has increased since the pandemic. As demand increases, so too do questions about whether these algorithms make fair and unbiased hiring decisions, or find the most qualified applicant. In this second episode of a four-part series on AI in hiring, we meet some of the big players making this technology including the CEOs of HireVue and myInterview--and we test some of these tools ourselves. This miniseries on hiring was reported by Hilke Schellmann and produced by Jennifer Strong, Emma Cillekens, Karen Hao and Anthony Green with special thanks to James Wall. Jennifer: Work… is a big part of our lives. It's how most of us pay our bills, feed our families… and put a roof over our heads. Michelle Rogers: "A permanent job would mean stability. You need something to keep you going and to keep you fresh." Dora Lespier: "Like being able to take my daughter being able to get whatever she needs. Henry Claypool: "You know, it's, it's a big part of my identity. It's what I do a lot.