In The Next Decade, AI Bias Will Do As Much Damage As Data Breaches
Data breaches are a terrible risk to enterprises. We run off data and a breach mean a failure in the commitment to safeguard data. It leads to hug costs to an enterprise; civil and sometimes criminal liability can follow. Allowing bias to creep into AI algorithms can have a similar destructive impact on the firm and, as I wrote this week on CIO.com, I believe that the next 10 years will prove that out.
An AI system is only as good as the data we provide it. If we’re providing it with biased data sets, it’s going to produce biased outcomes. Software engineers and project managers have to be conscious of this possibility and they have to work to prevent it. If the system starts with a clean data set, we can be confident that it will provide valuable assistance to a business organization.
Introducing Systemic Diversity
It’s probably not enough just to avoid biased data sets though. AI is a technology that’s designed to grow and evolve – we must work hard to ensure it can recognize the diversity of our society and organizations. Recently there have been stories in the news of facial recognition systems that have trouble with anyone that isn’t white and male. If we’re going to avoid these issues, AI systems must be introduced to as much diversity as possible.
Training and Testing
As humans, we aren’t born with personal biases and prejudice. These are things we develop over time as we’re influenced by our family, friends, and society. The same thing can happen in our AI systems if we’re not careful, no matter how much care we take to avoid it in development.
If we’re going to make sure that AI remains free from bias in our business systems, we have to be constantly re-evaluating and upgrading. Programmers must be trained to spot it and the average end user must have the tools to help correct it as well.
Automation Will Destroy Jobs – How Do You Get Organizational Buy In For That?
In his latest installment on his CIO.com column, Cloud Commerce Consulting CEO, Michael Zammuto talks openly about automation. Enterprise IT initiatives need business partners to succeed. But AI focuses on automation and that means job destruction along with productivity gains.
Many AI initiatives offer a new challenge. We have the ability to automate not just manufacturing, field, service and support jobs but, increasingly white collar, leadership and technology roles. He argues that this means AI will challenge the empires and possibly the careers of the very people you need to drive the initiative. In his article, he talks about innovation, buy-in and the reality of white collar automation.
Cloud Commerce Consulting CEO, Michael Zammuto wrote recently on his CIO.com column about the impact of data challenges on IT initiatives. Mike argues that many promising IT initiatives stall because they depend upon data being cleaned, enriched or combined as a precursor to success. BI and analytics projects are particularly dependent upon good data. Even with the best traditional tools and techniques, the process of preparing data for these projects does not scale well, often negatively.
This means trouble for IT chiefs and business sponsors alike. Mike argues that because machine learning algorithms can learn to categorize and clean data better as you as it processes more data, this means that AI is the only approach that scales data projects well.
Cloud Commerce CEO Michael Zammuto published a new article on CIO.com entitled 8 artificial intelligence technologies your enterprise needs today. The article is an executive summary and quick reference for CIOs and other functional, technology and business executives who are interested in understanding the most critical aspects of this crucial and transformative technology.
“AI” Is An Overloaded Term
Zammuto argues that the term “Artificial Intelligence” is an overloaded term. To insiders, academics and researchers this term is shorthand for general artificial intelligence which is the common view of AI as a system with intelligence that typically is modeled on biological cognitive systems. General AI is not a commercial product yet and is confined to research projects, predominantly.
Understanding The “AI Landscape”
Zammuto argues that, for enterprises, the term “AI” is more reflective of an “AI Landscape” that includes many interconnected technologies, available from a broad range of sources and vendors. Of these are ones that get a lot of media attention, including machine learning and automated assistants and chat bots, as well as less broadly appreciated technologies with massive potential including natural language generation and decision management.
How Small Businesses Can Use AI to Outrun The Competition
Cloud Commerce CEO Michael Zammuto recently published an article on artificial intelligence and related technologies. He argues that “AI” is often used an umbrella term for a shift to a digital-first strategy of automation and learning. He provides an overview of Machine Learning, Smart Robots, Virtual Assistants, Speech Recognition, Natural Language Generation and Decision Management as key technologies for most businesses.
Zammuto argues that unlike other major digital technologies, these collectively represent a disruptive force that can move too quickly for companies to safely adopt a fast-follower strategy. he points to Amazon using their data and technology advantages to simultaneously compete in diverse spaces against grocery stores, robotics companies and cloud providers as an example that these technologies can allow disruptive competition to come from unexpected outsiders.
He proscribes a strategy for small businesses to focus on using current analytics and data initiatives to gain operational advantage and then reinvesting that into commercial products like virtual assistants that can easily be adapted to a company. After that, small companies can further develop internal skills and expert connections to make additional, highly targeted and strategic investments.
Zammuto advises focusing on using virtual assistants followed by investments in NLG analytics platform to realize quick cost and performance benefits. with better data capabilities he suggests focusing on a single, potentially transformative, part of the business for another investment. Be the best at that thing, he argues, and gain a focused, impactful advantage in one area. This can be cost, service, product, quality, logistics or other areas but make sure it has the potential to change your position within your industry. This he concludes will start you on a virtual cycle of innovation and differentiated advantage that can make any small business a leader.
Michael Zammuto has launched a new blog focused on major technology trends and their impact on our future. This journal included writings on Artificial Intelligence, Automation and various policy issues. Please consider visiting,