Inside Collibra: Comparing your ethics framework to spicy foods

As technology grows, we've come to recognize the power of big data: how it influences company policies, consumer choices, and even government decisions. Data should not be just for profit — it should have an ethical and moral basis, which is where the importance of data ethics comes in. If you'd like to know more about data security and its ethical considerations, you're in for a treat this week. In this episode, Simla Sivanandan, Senior Manager of Data Intelligence at Collibra, joins us to talk about the importance of data ethics and how Collibra upholds data ethics within their organization. She also shares how the real problem is unconscious bias when dealing with machine learning (ML) and artificial intelligence (AI). Tune in to the episode to dive deeper into data ethics and unconscious bias.Here are three reasons why you should listen to this episode:Gain an understanding of what data ethics is all about.Discover the significance of unconscious bias in handling data.Find out how Collibra strategically instills data ethics within the company.ResourcesAn article on Lancaster University’s study on why weather forecasts were less reliable after the COVID-19 pandemicConnect with Simla over at LinkedInEpisode Highlights[01:20] Connecting Data and EthicsSimla initially found the concept of data ethics unnatural. Data is precise, while ethics are very subjective. Ethics may seem simple, like doing the right thing, but what’s right can differ for different people.Simla: “You see the power of data, where people are using that to make decisions that affect your life, your life quality, and all of that. So, we, as data professionals, always see the power of data. I think, as data citizens, it's our responsibility to use it ethically [and] wisely.”During the vaccine shortage at the start of the pandemic, the government used data to determine who was the priority, which has ethical implications.[04:45] Unconscious BiasData ethics is much bigger than machine learning (ML) and artificial intelligence (AI), which businesses use to personalize the customer's online experience.Companies must be aware of the purposes and risks involved in asking customers for their personal data.Simla: “To me, really, the gold standard is: If I'm working in a bank, am I comfortable banking with them? If I'm working in an insurance company, am I okay to purchase that? That kind of tells me: Am I okay with the way they are treating my data, right? That's where I am that it's not just ML or AI.”Simla believes that the conversation around ML and AI involves unconscious bias.There are cases wherein we have no control over the data, even if we understand why it’s happening.Unconscious bias is a vital conversation to have in data ethics.Simla: “Exclusion creates bias, and that might be unconsciously happening because we are not thinking through or we’re not picking a big enough sample set. That's where I'm coming from. So, it's always important as a data professional to be aware of this, right? As I limit my sample set, it can have unintended consequences, and we should address that.”[10:18] How Collibra Strategically Instills Data Ethics Collibra is guided by its core values: being open,...