Welcome to Certified Ethical Emerging Technologist or CEET. Emerging technology are technologies that allow us to manage extraordinary amounts and types of data. Areas such as data science, machine learning, artificial intelligence, and robotics are transforming how we do business and interact with society. Yet, issues of bias rising out of these technologies have impacted businesses, impacted individuals and entire populations. CEET is intended to empower a generation of ethical technologists who can promote ethics in all data-driven technologies, individuals who can turn ethical frameworks into actionable steps, leaders that can help organizations detect and mitigate ethical risks, and professionals who will communicate effectively about ethical challenges in data-driven technologies. CEET is designed for learners who want to create and lead ethical driven organizations. Whether you come from a liberal arts, business or computer science background. You have the foundation to complete the specialization. We have some incredible instructors to guide you along the way. First, let me introduce Eleanor 'Nell' Watson. Nell will be your instructor in modules in three courses, promoting the ethical use of data-driven technologies, turning ethical frameworks into actionable steps, and detecting and mitigating ethical risks. Nell is a researcher in machine vision and machine ethics and faculty at Singularity University. She has worked to forge ethical frameworks for organizations such as the IEEE and is collecting examples of behavioral norms to help socialize AI at her NGO EthicsNet. Welcome Nell. Thank you. It's a pleasure to be here. We're also joined by Renee Cummings. She will be your instructor for modules in three courses, promote the ethical use of data-driven technologies, detect and mitigate ethical risks, and communicate effectively about ethical challenges in data-driven technologies. Renee is an AI Ethicist, Criminologist and Criminal Psychologists. As an AI Ethicist, Renee is passionate about ensuring emerging technologies, a diverse, equitable, and inclusive, and advocates tirelessly internationally for AI that we can trust. Thank you so much. It's nice to be here. Thank you, Renee and welcome. We also have Tania De Gasperis, who will lead you through most of the first course in the CEET specialization, promoting the ethical use of data-driven technologies. Tania is a Researcher and Facilitator for the Montreal AI Ethics Institute and a member of the Adaptive Context Lab at OCAD University. She holds a Master of Design Degree in Strategic Foresight and Innovation. In her thesis work explored futures of inclusive and responsible AI. Welcome Tania and thank you. Thank you so much Megan. It's great to be here. Aaron Hui will be your instructor for modules in two courses, turn ethical frameworks into actionable steps and create and lead an ethical data-driven organization. Aaron designed and taught the first undergraduate course in AI Ethics under the Computer Science Department at UCLA, and is passionate about preparing the next generation to be ethically responsible leaders of technology. We have this amazing group of instructors and subject matter experts here with us today. Let's take the opportunity to dive in a bit deeper on the topics that we will be covering in the five courses in the specialization. Currently, we're in an era where bias, especially racial bias and the lack of diversity has the potential for greater inequities among populations, nations, genders, and races due to the prevalence of data-driven technologies like machine learning and AI. Now I want to ask you from your perspective, why is it so important to address bias in these emerging technologies? Machine learning systems are dependent upon data. They require examples from real life in order to understand the things they're looking at. Because that data comes from real life or real life examples, it naturally has all kinds of biases built into it. Biases from how humans have timed certain things or biases based upon the decisions that humans have made. There was a danger that these kinds of technologies can re-perpetuate existing biases, perhaps even making them worse than they were to begin with. This is one of the greatest risks of Machine Learning Technologies, and it's one of the areas that ethics is most particularly necessary. Thank you so much Nell for your perspective. Aaron, I want to get your perspective on another issue that is affecting our era of technology right now. Aaron, why do you think it's so important to address diversity in emerging technologies? Thanks Megan. In a rapidly globalizing world, the importance of asking how we can implement diversity, include more diversity in what we do, the importance cannot be overstated. It's one of the most important things that we can do when we begin to talk about how we want to approach ethics in artificial intelligence, emerging technologies, and all these diverse technologies, because this is a way that we can prevent ethnocentric bias, or mitigate some of the other biases that Nell was talking about earlier. By getting more people involved from across the world or across different cultures, we are able to access unique perspectives that we wouldn't have able to come up with or identify our own. With that being said, by including more people in what we do, we are ensuring that our technologies are more accessible to everyone, as well as making it more comfortable for people to use. I think that's very important to talk about. Absolutely. Thank you so much, Aaron for your perspective. Of course. Renee, I'm going to have you close out this part of the discussion. If we're not able to mitigate racial bias and diversify these data-driven technologies, where do you think society will see the greatest impact? Thanks Megan. I think society will see the greatest impact when it comes to justice and social justice, because the lack of diversity in issues such as racial bias, really undermine justice and equal access to resources, as well as just access to all the types of opportunities that are available in society. I think it will go a really long way in ending some of those old traditional and very ugly impartiality and inequities. I think what it will do is show vulnerable communities that they are being empowered, that they are being protected, and they are also given a chance at full citizenship. It also comes down to having a moral imagination. It's about social responsibility as well. It's also about really thinking about the meaning of humanity and also the meaning of citizenship. I think if we were to detect and mitigate those and really have a sustained way of ensuring that we take an ethical approach to data-driven technologies. We would have done a great deal for humanity. Well, I am very hopeful for all of that to occur with all of you as our instructors and for all of our learners.