Hi again, let me ask you something. What comes to your mind when you think of the word, ethics? For me, it's a set of principles to live by. Most people have a personal code of ethics that helps them navigate the world. When we're young, it could be as simple as never lie, cheat or steal, but as we get older, it's a much broader list of do's and don'ts. Our personal ethics evolve and become more rational, giving us a moral compass to use as we face life's questions, challenges, and opportunities. When we analyze data, we're also faced with questions, challenges, and opportunities, but we have to rely on more than just our personal code of ethics to address them. As we learned earlier, we all have our own personal biases, not to mention subconscious biases that make ethics even more difficult to navigate. That's why we have data ethics, an important aspect of analytics that we'll explore right here in this video. But first, let's go back to the general idea of ethics. While an exact definition is still under discussion in philosophy, one practical view is that ethics refers to well-founded standards of right and wrong that prescribe what humans ought to do, usually in terms of rights, obligations, benefits to society, fairness or specific virtues. Just like humans, data has standards to live up to as well. Data ethics refers to well- founded standards of right and wrong that dictate how data is collected, shared, and used. Since the ability to collect, share and use data in such large quantities is relatively new, the rules that regulate and govern the process are still evolving. The importance of data privacy has been recognized by governments worldwide and they started creating data protection legislation to help protect people and their data. The GDPR of the European Union was created to do just this. While policy makers continue their work, companies like Google have a responsibility to lead the effort and will do so in the same spirit we always have by offering products that make privacy a reality for everyone. The concept of data ethics and issues related to transparency and privacy are part of the process. Data ethics tries to get to the root of the accountability companies have in protecting and responsibly using the data they collect. There are lots of different aspects of data ethics but we'll cover six: ownership, transaction transparency, consent, currency, privacy, and openness. We'll explore data privacy and openness a bit later. First up is ownership. This answers the question who owns data? It isn't the organization that invested time and money collecting, storing, processing, and analyzing it. It's individuals who own the raw data they provide, and they have primary control over its usage, how it's processed and how it's shared. Next, we have transaction transparency, which is the idea that all data processing activities and algorithms should be completely explainable and understood by the individual who provides their data. This is in response to concerns over data bias, which we discussed earlier, is a type of error that systematically skews results in a certain direction. Biased outcomes can lead to negative consequences. To avoid them, it's helpful to provide transparent analysis especially to the people who share their data. This lets people judge whether the outcome is fair and unbiased and allows them to raise potential concerns. Now let's talk about another aspect of data ethics, consent. This is an individual's right to know explicit details about how and why their data will be used before agreeing to provide it. They should know answers to questions like why is the data being collected? How will it be used? How long will it be stored? The best way to give consent is probably a conversation between the person providing the data and the person requesting it. But with so much activity happening online these days, consent usually just looks like a terms and conditions checkbox with links to more details. Let's face it, not everyone clicks through to read those details. Consent is important because it prevents all populations from being unfairly targeted which is a very big deal for marginalized groups who are often disproportionately misrepresented by biased data. Next, there's currency. Individuals should be aware of financial transactions resulting from the use of their personal data and the scale of these transactions. If your data is helping to fund a company's efforts, you should know what those efforts are all about and be given the opportunity to opt out. The last two aspects of data ethics, privacy and openness, deserve their own spotlight on this data stage. Coming up, you'll see why.