Embracing AI is wonderful. From a practical business perspective, though, there are limits. This issue is broader than AI. However, I’ll constrain the conversation to that for now, given the attention AI is getting these days. Yes, some processes are undoubtedly good candidates for automation, but avoiding “technocentrism” is critical to
AI has captured the general public's imagination, so it was no surprise that it was nearly the only topic of conversation among data professionals at this year’s Chief Data and Analytics Officer (CDAO) conference in London. Of course, AI and machine learning are not new concepts for those working in
AI – just like humans – can carry biases. Unchecked bias can perpetuate power imbalances and marginalize vulnerable communities. Recognizing the potential for bias is one of the first steps toward responsible innovation. Doing so allows users to include diverse needs and perspectives in building inclusive and robust products. Through
As organizations embrace AI, they often handle large volumes of data that power AI systems. Handling data appropriately includes implementing adequate privacy policies and security measures to protect it. Doing so prevents accidental exposure and ensures ethical data use. AI technology often uses sensitive data for creating, training and utilizing models.
As AI rapidly advances over the next several years, I’ve been fortunate to have an active role in helping to guide a responsible path forward when it comes to technology’s impact on our daily lives. Currently, this role includes serving as Vice President for the SAS Data Ethics Practice, as an
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What do you get when you mix leaders from every industry, a hall-of-fame basketball coach and a best-selling author together in three days? SAS Innovate in Orlando, of course. As organizations navigate this changing economic landscape, many are turning to analytics and AI to help them stay ahead of the
Who is responsible for ensuring that new AI technologies are fair and ethical? Does that responsibility land on AI developers? On innovators? On CEOs? Or is the responsibility more widespread? At SAS, we believe that it is everyone’s duty to innovate responsibly with AI. We believe that adhering to trustworthy
I see the term resilience in a lot of business literature these days. Intuitively, it makes sense. After a pandemic, global supply chain disruptions and resulting economic fragility, executives understandably consider adaptability, durability and how best to operate with a strength of character – all attributes that define resilience. Many
Artificial Intelligence (AI) can drive environmental innovation (EI) in sustainability and reduction of carbon emissions. However, the use of AI itself also comes with environmental costs. The high computational requirements of AI-based systems lead to significant energy consumption, contributing to greenhouse gas emissions. The energy consumption of AI systems can
If you’ve ever contemplated AI's messy reality and political nature, the interplay of technology with society and the impact of AI on democracy, we have a conversation for you. As AI rapidly expands, it has sparked numerous discussions and debates. One theory is that AI is inherently political. This viewpoint
In today's world, data-driven systems make significant decisions across industries. While these systems can bring many benefits, they can also foster distrust by obscuring how decisions are made. Therefore, transparency within data driven systems is critical to responsible innovation. Transparency requires clear, explainable communication. Since transparency helps people understand how
Generative AI (GenAI) is a category of AI that can create new content, including video, audio, images and text. GenAI has the potential to change the way we approach content creation. It’s gotten much attention lately. Take ChatGPT for example. The AI chatbot has captivated the public’s imagination with clever
In this post, Ajay Agrawal, professor at Toronto's Rotman School of Management, discusses the challenges of unlocking the full potential of AI and ML for businesses and banks. Agrawal explains how the taxi industry in London, UK provides a cautionary tale of the potential impediments to driving value from AI,
Responsible innovation is critical because technology does not exist in a vacuum. It affects us all in unexpected ways. We know analytics has an undeniable impact on society. For example, analytics can help hospitals manage their inventories for essential items like wheelchairs and bladder scanners, help sports teams curate a
One of the reasons I got involved with the trustworthy AI movement is because automated systems enabled by our past will hurt people – at scale – if we aren’t careful. Worse yet, and from a personal perspective, it concerned me that if such systems were deployed in justice and
I’ve spent months traveling and speaking to business leaders worldwide about trustworthy AI and responsible innovation. On the nights I laid awake in unfamiliar hotel rooms, wishing my body clock would adjust faster than it was, I found joy in watching local television in local languages. While I don’t understand
More digital channels are bringing greater connectivity and more data is bringing added complexity to organizations. All this can feel chaotic or like a fog of information warfare. As a result, the pace of disruption and data expansion require visual tools that accelerate data wrangling and modeling. To overcome complexity,
As head of the SAS Data Ethics Practice, I spend a lot of time contemplating the social implications of AI. Considering its benefits like augmenting medical decisions and pitfalls, making decisions based on biased data results in dire consequences for patients. Such implications have the potential to impact society in a variety
Students at North Carolina State University completed design projects yielding striking visuals, purpose and functionality without unethical design characteristics. If you were to design the ultimate vacation home, you would most certainly consider options and features that speak to your individual preferences and style. It turns out that same inclination
We hear a lot about responsible AI or AI ethics in the marketplace today. At SAS, we believe there should be a larger conversation about responsible innovation. In reality, the decisions made by AI are the outcome of algorithms, data and business processes. This means ethical considerations must be applied
