Collaborating Authors

Social & Ethical Issues

Council Post: Formidable Human-AI Relations Can Accelerate Sustainability Efforts


AJ Abdallat is CEO of Beyond Limits, a leader in artificial intelligence and cognitive computing. Artificial intelligence (AI), machine learning (ML) and similar digitalization solutions are modifying the way the world's most influential companies and industries -- as well as entire cities -- function every day. When working in harmony with humans, AI and other automation systems have the potential to make huge impacts on economic growth across the globe, going so far as to support solving humanity's most critical roadblocks, from streamlining energy production to improving grid systems and achieving more sustainable operations for nearly every major industry on Earth. As the CEO of an AI company making advanced digitalization software products and solutions, the paradigm of enabling people and AI to work together on achieving more sustainable operations is always top of mind; its importance cannot be curbed. As we move into the future, I'm confident there will be plenty of jobs for both humans and AI so long as they are able to function in conjunction with one another.

Why we Need Art to Cocreate the Societal Impact of AI


The societal impact of Artificial Intelligence (AI) dwarfs its technological impact. Already, we see AI everywhere in our daily lives; we see it in our grocery shopping app, our entertainment streaming lists, social media feeds, our dating lives, and the list goes on. The use of AI has become so naturally intertwined with our lives that we often forget to think about the future. We should ask ourselves the question of how we can unlock AI's full potential while keeping its risks at a minimum. And to investigate this question, we need to work together.

How to Respond to the Future of Work: The Importance of Upskilling


How are you evolving your skills for the future of work? This is one of the most pertinent questions workers are asking themselves. However, the answer is constantly changing. With every new technology, innovation, regulation, and system, the most in-demand skills shift. The capabilities that employers are looking for today are no longer the capabilities of last year, and in many industries this has created a significant skills gap.

How do we keep bias out of AI?


From the coining of the term back in the 1950's to now, AI has taken remarkable leaps forward and only continues to grow in relevance and sophistication But despite these advancements, there's one problem that continues to plague AI technology – the internal bias and prejudice of its human creators. The issue of AI bias cannot be brushed under the carpet, given the potential detrimental effects it can have. A recent survey showed that 36% of respondents reported that their businesses suffered from AI bias in at least one algorithm, resulting in unequal treatment of users based on race, gender, sexual orientation, religion or age. These instances incurred a direct commercial impact: of those respondents, two-thirds reported that as a result they lost revenue (62%), customers (61%), or employees (43%). And 35% incurred legal fees because of lawsuits or legal action.

How to use responsible AI to manage risk


We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. While AI-driven solutions are quickly becoming a mainstream technology across industries, it has also become clear that deployment requires careful management to prevent unintentional damage. As is the case with most tools, AI has the potential to expose individuals and enterprises to an array of risks, risks that could have otherwise been mitigated through diligent assessment of potential consequences early on in the process. This is where "responsible AI" comes in -- that is, a governance framework that documents how a specific organization should address the ethical and legal challenges surrounding AI. A key motivation for responsible AI endeavors is resolving uncertainty about who is accountable if something goes wrong.

Why are we failing at the ethics of AI? A critical review


Anja Kaspersen and Wendell Wallach are senior fellows at Carnegie Council for Ethics in International Affairs. In November 2021, they published an article that changed the AI ethics conversation: Why Are We Failing at the Ethics of AI? Six months later, the questions the article raised are no closer to resolution. This article was a don't-hold-your-punches review on the state of AI ethics, with which I am in almost complete agreement. If we want to advance the AI conversation, this is still a good place to start. I've quoted a portion of their article, with my comments interspersed: While it is clear that AI systems offer opportunities across various areas of life, what amounts to a responsible perspective on their ethics and governance is yet to be realized.

Artificial Intelligence: The Science Behind The Good Customer Experience - Elets BFSI


Artificial Intelligence (AI), as one of the leading technological trends, continues to grow in popularity among marketers and sales professionals, and has evolved into an essential tool for brands seeking to provide a hyper-personalized, exceptional customer experience. AI-enhanced customer relationship management (CRM) and customer data platform (CDP) software is now available, bringing AI to the enterprise without the high costs previously associated with the technology. On the basis of exclusive interactions with leaders in the BFSI sector, Nidhi Shail Kujur of Elets News Network (ENN) explores how with constantly evolving technologies, the banking and financial services industry promises to exceed customer expectations. The banking industry is undergoing significant change, particularly with the spread of customer-centricity. We live in a world where the majority of people have access to the internet.

Steve Blank Artificial Intelligence and Machine Learning– Explained


Hundreds of billions in public and private capital is being invested in Artificial Intelligence (AI) and Machine Learning companies. The number of patents filed in 2021 is more than 30 times higher than in 2015 as companies and countries across the world have realized that AI and Machine Learning will be a major disruptor and potentially change the balance of military power. Until recently, the hype exceeded reality. Today, however, advances in AI in several important areas (here, here, here, here and here) equal and even surpass human capabilities. If you haven't paid attention, now's the time. Artificial Intelligence and the Department of Defense (DoD) The Department of Defense has thought that Artificial Intelligence is such a foundational set of technologies that they started a dedicated organization- the JAIC – to enable and implement artificial intelligence across the Department. They provide the infrastructure, tools, and technical expertise for DoD users to successfully build and deploy their AI-accelerated projects. Some specific defense related AI applications are listed later in this document. We're in the Middle of a Revolution Imagine it's 1950, and you're a visitor who traveled back in time from today. Your job is to explain the impact computers will have on business, defense and society to people who are using manual calculators and slide rules. You succeed in convincing one company and a government to adopt computers and learn to code much faster than their competitors /adversaries. And they figure out how they could digitally enable their business – supply chain, customer interactions, etc. Think about the competitive edge they'd have by today in business or as a nation. That's where we are today with Artificial Intelligence and Machine Learning. These technologies will transform businesses and government agencies.

Finding the Fairness in AI


Explains Nikola Konstantinov of Switzerland's ETH Zürich, "Fairness in AI is about ensuring that AI models don't discriminate when they're making decisions, particularly with respect to protected attributes like race, gender, or country of origin." As artificial intelligence (AI) becomes more widely used to make decisions that affect our lives, making certain it is fair is a growing concern. Algorithms can incorporate bias from several sources, from the people involved in different stages of their development to modelling choices that introduce or amplify unfairness. A machine learning system used by Amazon to pre-screen job applicants was found to display bias against women, for example, while an AI system used to analyze brain scans failed to perform equally well across people of different races. "Fairness in AI is about ensuring that AI models don't discriminate when they're making decisions, particularly with respect to protected attributes like race, gender, or country of origin," says Nikola Konstantinov, a post-doctoral fellow at the ETH AI Center of ETH Zürich, in Switzerland. Researchers typically use mathematical tools to measure the fairness of machine learning systems based on a specific definition of fairness.

Skills and security continue to cloud the promise of cloud-native platforms


Joe McKendrick is an author and independent analyst who tracks the impact of information technology on management and markets. As an independent analyst, he has authored numerous research reports in partnership with Forbes Insights, IDC, and Unisphere Research, a division of Information Today, Inc. The KubeCon and CloudNativeCon events just wrapped up in Europe, and one thing has become clear: the opportunities are outpacing organizations' ability to leverage its potential advantages. Keith Townsend, who attended the conference, observed in a tweet that "talent and education is the number one challenge. I currently don't see a workable way to migrate thousands of apps without loads of resources. Information technology gets more complex every day, and there is no shortage of demand for monitoring and automation capabilities the build and manage systems. Cloud-native platforms are seen as remedies for not only improved maintenance, monitoring, and automation, but also for modernizing ...