A framework to Audit AI for trust, ethics, and bias


Disclaimer: This is a personal blog. Any views or opinions represented in this blog are personal and belong solely to the blog owner and do not represent those of people, institutions or organizations that the owner may or may not be associated with in professional or personal capacity, unless explicitly stated.


Note: I can talk about this topic all day. But I have kept the scope to the highest level to ensure that the ideas in this article are easier to grasp. I will be posting more articles that delve into details on how organizations can audit for trust, ethics, & bias.


Artificial intelligence (AI) requires humans to set up rules that will be coded by programmers. These rules will dictate how the various AI systems will operate within society and drive value for organizations. Many people tend to think AI is very sophisticated and beyond comprehension, and they throw buzzwords around such as “machine learning,” “natural language processing (NLP),” and “deep learning.” Let me try to explain the most popular AI systems:

  • Machine learning relies on programmers coding the rules of a process within a system so that the machine can execute these rules systematically, along with learning new things along the way. The learnings of such a program can be endless if proper constraints aren’t set.
  • Neural networks figure out the rules themselves like an infant would as they get older and are exposed to the environment around them. The way neural networks do this is called “deep learning.”
  • NLP, Image & speech recognition takes the world around us, which is messy and unstructured, and feed this data to a computer with a lot of dimensions. The computer will then try to see patterns that we could not easily see, or try to gather understanding of events that was not explainable and based on the data and dimensions programmed will provide decisions in real- time, and make predictions about the future.

With all that said, I’d like to get to the point of my post. AI is doing amazing things, and compelling use cases are being identified. However, using AI requires trust. Trust is essential when it comes to technology making decisions that have an impact on people’s lives. And with technology being given this power to make decisions, companies and governments need to demonstrate that their technology is free from their bias and has good ethics embedded in the technology.

It is challenging to demonstrate trust, ethics, and bias when it comes to using the various types of AI, but we will have to start somewhere. Over the last year, there have been numerous reports and fines related to the use of AI, such as:

Based on the growing number of incidents, it has become imperative that leaders on boards of major organizations be able to provide answers to regulators, customers, and the general public on the following questions:

  • What is your company using AI for, and what was it optimized to do? Leaders need to be able to clearly explain what their AI is optimized for when it comes to AI effectiveness. AI that is used to grant credit card approval, for example, along with setting interest rates for clients, will be optimized to ensure that the company manages their risk effectively by offering proper credit limits and interest rates to individuals who are considered low-risk. This sounds fine on the surface, but if we were to take a closer look, the optimization factor would provide a higher credit limit and favorable interest rates to wealthy individuals because they have multiple assets, low-risk ratings, and wider access to credit. On the other hand, individuals considered vulnerable (e.g., immigrants, women, people of color, low-income individuals) will receive higher interest rates, lower credit limits, or a credit card denial due to the fact that they do not have wide access to credit. This would demonstrate bias in the way the AI was programmed and the variables used to favor applicants of a higher social class and an ethical problem where you are discriminating against a certain class of applicant, gender and social standing, along with the values of your company (diversity, inclusion, etc.), which would diminish trust.. Organizations need to clearly understand what their algorithms are optimized for and be ready to accept the tradeoffs.
  • What were your tradeoffs?  If you designed an algorithm like the one above, what did you sacrifice to ensure the AI worked at 100% efficiency? Did you sacrifice customer privacy by feeding the AI system with numerous variables pertaining to the user across multiple product lines? Was the data source reliable, and can the lineage be traced? An AI system has no human emotions and will make decisions strictly based on the logic programmed. Additionally, the scenarios of your AI system will need to be understood as it relates to the variables not considered during the programmining and the tradeoffs you are willing to accept should those scenarios occur.
  • Were there any biases, and how can you demonstrate this? Bias is everywhere, and we all have them. Behavioral economists have confirmed that humans are susceptible to several cognitive biases. If you take the time to observe the countless instances of irrational human behavior all around you, you will realize that these biases are everywhere. Leaders should be ready to explain how their system is free from bias and whether the AI systems’ decision variables were challenged, and assessed, by independent parties for bias, and the conformity to design.

A framework to audit AI

Based on some research I conducted, I have developed a high-level framework on how to audit AI for trust, ethics, and bias. This framework is meant to serve as a starting point and can be adapted as needed.

https://lorenzonagreadiecom.files.wordpress.com/2019/11/ai-framework-1.jpg?w=1024
Developed and created by Lorenzo Nagreadie

In short, using AI has a lot of merit and will allow people to do more value-added work, but AI will only succeed on a foundation of trust. With the framework above it provides leaders an approach on how they can go about understanding what their exposure is as it relates to AI and their use of them. The time has come where leaders in major organizations need to be aware of:

  1. The exposure if their AI algorithms fail and obligations to fulfill their duties?
  2. The use of their AI algorithm is legal, ethical, and responsible?

A practical guide to creating a culture of innovation

Innovation is necessary to stay competitive in today’s market as a company and as an individual. I have heard of many promising innovations or transformations undertaken by organizations and departments that end up in failure. The reason for failure? Adoption, the vision did not resonate, people did not understand, it didn’t stick, and many more. This guide is to get to the root of why your big idea did not stick with people and how to get people to generate innovative ideas.

1.    Communicate a compelling narrative about the vision: Let’s say a department or organization communicates the following vision: “We will grow our company by being innovative and adding value to consumers.” What’s wrong with this statement? Nothing. However, we need to effectively tell a story about how the vision resonates with the individual’s cause and how it effectively adds value. The organization’s vision is something the individual should feel strongly about that he or she will forego the competitor organizations’ salary to be part of the journey to create something amazing. Facebook, for example, has done a great job of communicating their vision and mission. Facebook’s mission is “to give people the power to build community and bring the world closer together.” People use Facebook “to stay connected with friends and family, to discover what’s going on in the world, and to share and express what matters to them.” Facebook continuously innovates and makes strategic acquisitions to further this vision. Anyone I have met at Facebook believes in and connects with the vision that they work countless hours and defend the company through troubled times. If you want people to be innovative and bring their organizations to success during transformations, it is imperative that you clearly and effectively communicate that vision and align it to their personal mission.

2.    Foster trust: To try new things you need to have an environment where an individual feels empowered to speak up, try new things, raise their hand and ask for help. We do so with the confidence that our boss or colleagues will be there to support us. Let me quote Brene Brown: “Trust is the stacking and layering of small moments and reciprocal vulnerability over time.” When trust is not built we often feel forced to lie, hide mistakes, act as if we know how to do something (when we really don’t know), and fail to admit that we need help out of fear of humiliation, reprisal or finding ourselves on the shortlist of a layoff. American Airlines is a perfect [bad] example where the employees did not have the trust of their teams to feel empowered to do what is right and speak up while a passenger was being dragged out of the plane like an animal. Trust is when an individual shows up to work and can be his or her authentic self and feel empowered. His/her managers provide support and continuously have open conversations about elevating people versus improving the numbers or walking around and trying to catch you doing something your not supposed to.

3.    Have worthy rivals: Simply said, your rivals will show you where your weaknesses lie. You cannot be your best self or bring innovative ideas forward if you think you are the best and avoid being in situations where you are challenged. This leads you to accept the status quo and be crushed by your rivals. It is crucial to have a worthwhile rival to keep you on your toes and force you to confront your weaknesses so that you can address them and elevate yourself. You might be someone’s rival right now and that person may be putting in the hard work to address his or her weaknesses. Innovation requires a healthy dose of rivalry to generate innovative thinking and ideas.

4.    Have flexibility to pivot – Not all ideas are a success. You need to have the flexibility to change direction when you feel the value is no longer there. If the environment has incentives that measure success on outputs, you will not have great ideas. You will have compliance to meet those numbers. The environment should be such that it allows you to blow up your idea before someone else does. Companies demonstrate this by continuously blowing up their business before the market does, even when they were at their peak. Netflix did this by blowing its idea of delivering DVDs by mail to streaming, and Apple did this by entering the personal computing space. These companies did not go down the same path. They realized that, despite having a good idea, they needed to pivot to a better idea that will generate more value. Yes, it will be hard, but this is why you need to ensure the vision is communicated effectively and trust is embedded within your teams to handle the stress this is going to bring.

5.    Have the courage to lead: Leading may sound easy but it is far from it. Leadership is a lifestyle. It is thankless and solitary. You do not become a leader by attending an offsite or company event. You need to invest in the growth of others. Results are not immediate and you will often feel like no progress was made. You will need to continuously show up and lead others to see that vision. Lead at the front of change and practice extreme ownership.

6.    Live with a growth mindset: Nothing is a failure; it’s just an option that did not work at that time. Failure gives us time to re-group and apply new thinking to a problem. Innovation is hard, especially when it is so broad that many will not see the value early on. But going through this you will learn and incrementally get better at putting the best, innovative idea forward. Many leaders will share how many times they failed, but they just figured out that they need to keep trying a different approach if they believe in their mission. Always see things from a different perspective and change the narrative to yourself. Many departments have audacious goals and many cannot see the benefit of how they will get there. All they happen to see are the failures and the insanity around the ideas. But if we were to change our perspectives, we’d be forced to think broader and challenge ourselves, perhaps gain technology fluency, participate in something world-class and get a free education while we’re at it.

I’m mindful that the list I outline here is not exhaustive. But at least it’s something to start with when it comes to creating a culture where you are empowering people to be innovative.

This post was inspired by Simon Sinek.