Our guest this week is Dawn Harpster, Senior Conversation Architect at Talkdesk. Dawn is actively committed to the extinction of bad IVR and Virtual Agent experiences. Her passion for the nuances of human behavior, conversation, and technology lead her to a career in human to machine interaction design; evangelizing simplicity, clarity and great user experience. Dawn has worked with a variety of high profile clients including Apple, Alaska Airlines, Direct TV and Western Union. She has also worked as a TV engineer, writer/producer, a program director at a homeless shelter and a professional jouster. Topics discussed include: • What and where Conversational AI is • Conversation design principles • Challenges and opportunities of being a woman working in AI Links: • LinkedIn Profile: https://www.linkedin.com/in/dawn-harpster-4b3130b/ • Women in AI Blogs: https://blog.re-work.co/tag/women-in-ai/
Our guest this week is Jen Wang, Senior Manager of Data Science at Wayfair. Jen joined the Wayfair team in 2016 and leads multiple teams of data scientists that develop customer-scoring, uplift modeling, and reinforcement learning systems to optimize marketing decisions at Wayfair. Prior to this she received her Ph.D. in Biophysical Chemistry from the University of Iowa, where she researched cancer-related drug development. Topics discussed include: • Starting a career in AI • Academia vs Industry • Workplace changes due to COVID-19 • Advice for a career in STEM • Female role-models Links: • LinkedIn Profile: https://www.linkedin.com/in/jenzhenwang/ • Women in AI Blogs: https://blog.re-work.co/tag/women-in-ai/
Our guest this week is Merav Yuravlivker, the Co-Founder and CEO of Data Society, a company passionate about increasing data literacy on a global scale so that organizations and their employees can be smarter about data. Since starting Data Society in 2014, Merav has empowered thousands of professionals with new data science skills, and is dedicated to giving others the tools to approach problems strategically and build a community to answer the question "How can data science change the world?". Topics explored include: • Breaking down barriers in education • Increasing diversity in Data Science • A data-driven culture • Trends in the world of Data • Data literacy Links: • LinkedIn Profile: https://www.linkedin.com/in/meravyuravlivker/ • Data Society: https://datasociety.com/
Our guest this week is Mari Joller, Founder and CEO of Snackable AI, a content discovery engine for the audio-first world. Mari has worked in the audio ecosystem for a number of years, including founding her previous startup Scarlet, as well as building and scaling products at Virgin Mobile and Nokia. Audio content is on the rise. What role does artificial intelligence have to play? Topics explored include: The shift in NLP and conversational and speech based technologies to becoming more mainstream The process of using AI to add structure and metadata into spoken word content Challenges faced when building the product The future of voice-based technology in the AI space and in the wider business context The changing landscape of how people consume and digest content
This week we're joined by Ritika Gunnar, VP of Data & AI Expert Labs at IBM. Ritika is one of IBM’s leading voices on trustworthy AI. Her team helps organizations embed principles and tools that build trust across the AI lifecycle, from preparing the data and building the model to deploying and managing it in real-time. As AI infiltrates almost every aspect of our lives, the lack of trust has never been a more pressing issue. Topics explored in the conversation include: • COVID-19 and a shift in the importance of trust; • The challenge of trust from a technology, education, management and culture perspective; • Ensuring explainable plus trustworthy AI; • The challenges of deploying models both responsibly and at scale; • Starting a career in AI; • COVID-19 and the impact of women in AI Links: • LinkedIn Profile: https://www.linkedin.com/in/ritika-gunnar-4b4542/ • Upcoming events on Responsible AI & Trust: https://www.re-work.co/events/topics/ai-for-good
This week's guest is Rachel Alexander, CEO and founder of Omina Technologies, an AI company dedicated to ethical AI solutions. Rachel is responsible for the technological vision and strategy of Omina Technologies and recently won the award for ‘Artificial Intelligence Person of the Year’ in Belgium, where she has lived and worked for the past twenty years, devoting herself to helping companies navigate new technological advances and incorporating them into their strategy. Topics explored in the conversation include: • What does ethical and trustworthy AI mean to you? • Why should companies should invest in ethical and trustworthy AI? • How can we ensure AI is accessible to all? • What is the biggest challenge faced by organisations regarding explainable AI? • How do different industries differ in working towards explainable AI? • Has COVID had an impact on accelerating or hindering ethical and trustworthy AI? Links: • LinkedIn profile: https://www.linkedin.com/in/rachelalexander777/ • Omina Technologies: http://ominatechnologies.com/ • View upcoming events on Ethics here.
This episode features Lucy Vasserman, Staff Software Engineer at Google. Lucy leads the Conversation AI team within Google's Jigsaw, which studies how computers can learn to understand the nuances and context of abusive language at scale. More specifically, Lucy works on machine learning research to improve core models, which power the Perspective API, with a focus on combating algorithmic bias. She also collaborates with internal and external users to ensure the Conversation AI models capture their needs. Topics explored include: • Computer Science Careers • Conversational AI • Algorithmic Bias • Ethical AI • Fair & Safe Technology • Large Language Models Links: • LinkedIn profile • Perspective API:https://www.perspectiveapi.com/ • The Current: https://jigsaw.google.com/the-current/toxicity/ • View upcoming events here
This episode features Natasha Jaques, Research Scientist at Google. Natasha Jaques recently finished her PhD at MIT, which focused on improving the social and affective intelligence of deep learning and deep reinforcement learning. She is now a Research Scientist at Google Brain and Berkeley working with Sergey Levine and Doug Eck. Topics explored include: • Social Reinforcement Learning • Multi-Agent RL Algorithms • PAIRED • Deep Reinforcement Learning • Applications of Reinforcement Learning • The future of Reinforcement Learning • Computer Science Careers View the video edition here! Links: • LinkedIn profile: https://www.linkedin.com/in/natashajaques • Twitter profile: https://twitter.com/natashajaques • Video edition: https://youtu.be/_gLU5Uw4TWU • View upcoming events here: https://www.re-work.co/
This episode features Susanna Dillenbeck, Commercial Partnerships Manager at Furhat Robotics, a startup based in Sweden, with a mission to enable a revolution in human-computer interaction through social and conversational robotics. Susanna focuses on creating collaborations to help them bring more applications to life on the Furhat platform. Topics explored included: • The meaning of Conversational AI and Social Robotics • The positive impact of Social Robots for businesses and society • The challenges faced with Social Robotics • Gender and Social Robotics • The issue of being emotionally connected to machines • The future of emotion AI • Women in AI challenges • Advice for women in AI coming from a non-technical background Links: • LinkedIn Profile: https://www.linkedin.com/in/susanna-dillenbeck/ • View upcoming events on Conversational AI here: https://www.re-work.co/events • Read the transcript in full here: https://blog.re-work.co/social-robotics-and-conversational-ai-with-susanna-dillenbeck
This week's guest is Tamanna Haque, Senior Data Scientist at a global automotive company. Her focus is to couple analytics and AI to support intelligent driving, and to apply AI to create new products and services, improve customer experiences, streamline operations and update business strategy. Topics explored included: • Can you give us an overview of your work in AI? • How can data science, modelling and forecasting techniques be applied to assist to a shift to a shorter-term focus on insights & business strategy? • What are the main organisational challenges in shifting to a shorter-term strategy? • What's the connection between AI vs Analytics, and where do the lines perhaps blur? • Why is the representation of women so important in data science and how businesses can improve this? • What impact has COVID-19 had on Women in AI/DS, over the past 12 months? • Do you have any role-models or women in the sector that have inspired you in your career? • What would be your tips to anyone wanting to start working in AI, or develop their career? Links: • LinkedIn Profile: https://www.linkedin.com/in/tamannah1/
This week’s guest is Myrna MacGregor. Myrna Macgregor leads BBC thinking on responsible AI/Machine Learning. She is focused on developing the right tools and resources to incorporate the BBC’s values and mission into the technology it builds. As a public policy specialist, she is particularly interested in work on AI/ML fairness, transparency, and accountability. Here are the questions we asked Myrna: 1. Can you tell us a bit more about yourself and your current role at the BBC? What led you here? 2. Can you please share a bit more about your background and career journey? 3. Can you tell us a little more about how you started building the BBC’s own framework (the Machine Learning Engine Principles and Checklist) and how you identified the tenets that needed to be considered in terms of promoting the Responsible use of AI? 4. What are the challenges of turning ethical principles into practice? 5. If you could share any tips or tricks for anyone starting out their careers within the field of AI and in particular, who has an interest in supporting the responsible development of technology, what would it be? 6. Where can our listeners keep up with you? Watch the YouTube video of the podcast here. Links: • LinkedIn Profile: https://www.linkedin.com/in/myrna-macgregor-17759b144/ View additional videos on Explainable AI in the playlist here.
This week's guest is Alisha Arora is an ambitious 14-year-old on a mission to leverage exponential technology to solve some of the world’s largest problems. She is an advocate for mental health and is currently researching at MIT’s AI lab to diagnose and prevent suicide with machine learning. She has also founded her own non-profit organization, The HopeSisters, with a mission to support children in foster care which has gained recognition across global media. Topics explored in the podcast include: • As a teen why does mental health matter to you? • Why do you think machine learning is the solution? • How did you get involved with Machine Learning? • Why should youth start getting involved with machine learning right now? • Do you think Governments and Educational Institutions are providing enough information about AI as a potential area for work to young people just now? • What advice would you give someone young who wants to start getting into AI? • As a youth, what do you think is the potential of AI in the future? • How do you overcome challenges when building ML models? • Why should more people get involved with AI and mental health? Links: • The HopeSisters: https://www.thehopesisters.com • LinkedIn Profile: https://www.linkedin.com/in/alishaarora56/ Watch the YouTube video of the podcast here. View all upcoming events here, including the AI in Healthcare & Pharma Virtual Summit taking place in March 2021.
This week's guest is Juliet Waters, Chief Knowledge Officer at Kids Code Jeunesse, a Canadian charity with a mission to give every Canadian child access to digital skills education, with a focus on girls and underserved communities. KCJ teaches kids and their educators about topics including algorithm literacy and artificial intelligence, and how these integrate with the UN’s Sustainable Development Goals to give kids the confidence and creative tools they need to build a better future. Topics explored in the podcast include: • You recently launched the #kids2030 Challenge, to encourage kids to use data science to address plastic pollution. What has the response been to the challenge so far? • Can you share more about the reasons behind The Algorithm Literacy Project and its goals? • What has the response been from adults, parents and teachers? • Have there been any challenges? • Do kids often show more interest in pursuing a career in AI after being involved in your work? • How has COVID19 impacted KCJ? • What are your thoughts on the challenges faced by women as AI practitioners? If you're keen to learn more about Kids Code Jeunesse and The Algorithm Literacy Project then please do check out the links below. Links: • Kids Code Jeunesse: https://kidscodejeunesse.org. • The Algorithm Literacy Project: https://algorithmliteracy.org/
This week's podcast is sponsored by our partner GSI Technology, and our guest this week is their Lead AI Scientist, Daphna Idelson. Daphna has a Computer Engineering degree from the Technion Israel Institute of Technology and extensive industry experience in specialized video processing, deep learning algorithms, CNN, distance metric learning, and large-scale similarity search. At GSI Technology, Daphna applies her expertise to ground-breaking power/performance solutions with the Gemini Technology and Associative Processing Unit. Topics explored in the podcast include: • Can you explain a bit about your current research focus? • Can you give an overview of your recent findings in accelerating Similarity Search? • What are the next steps for this research area? • Can you share an overview of your recent experience in taking part in a Radar Spectrogram Classification challenge hosted by the Israeli Ministry of Defense R&D directorate? • What are your predictions for advancements in CV and Image Processing? • What prompted you to begin a career in AI? • What advice would you give to anyone looking to get into a career in AI? • What challenges have you faced as a woman working in AI? • Have role models been a factor in your career? Read the transcript here. Founded in 1995, GSI Technology, Inc. is a leading provider of semiconductor memory solutions. GSI's resources are focused on new products that leverage the strengths of its market-leading SRAM business. The Company recently launched radiation-hardened memory products for extreme environments and the Gemini APU, a memory-centric associative processing unit designed to deliver performance advantages for diverse AI applications. The APU's architecture features massive parallel data processing with two million-bit processors per chip. The massive in-memory processing reduces computation time from minutes to milliseconds, even nanoseconds, while significantly reducing power consumption with a scalable format. Headquartered in Sunnyvale, California, GSI Technology has 172 employees, 114 engineers, and 92 granted patents. Learn more about GSI Technology and their advancements via https://www.gsitechnology.com/APU.
Our guest this week is Avriel Epps Darling, researcher, entrepreneur and artist, and currently, a PhD student at Harvard's Graduate School of Education, seeking to make meaningful impact through researching how online, machine learning-driven ecologies influence youth of colour as they construct and affirm racialized and gendered identities. Avriel has received numerous awards and honours including an invitation from the U.S. Department of Education to present her work for Congress as well as recognition as part of the top 10% of undergraduate social scientists in the world. Today, her research, in partnership with organizations such as Spotify and Snap Inc, focuses on the intersection of algorithmic bias in content recommendation systems, and racial identity development. Topics explored included: • Can you share more about your current research focus to start with? • In your paper on Artist Gender Representation in Music Streaming, your findings show that about 1 in 5 streams go to female artists. How have music recommendations influenced this? • What is the role of streaming services for challenging inequities by spotlighting underrepresented artists in their recommendations? • Can you share more about your findings when researching the relationship between the proportion of female artists streamed on programmed playlists and the proportion of female artists listened to organically. And how this is impacted by the user gender and age? • Can you share more on the challenges of gender labelling? the challenges of gender labelling? • What are the next steps for this research area? • Has your background influenced your academic research? • What advice would you give to anyone looking to get into a career in AI currently? Inspired to explore further? View our upcoming event on Ethics & Social Responsibility here. You can connect with Avriel via LinkedIn and Twitter.
Our guest this week is Madhurima Khandelwal, Vice President and Head of American Express AI Labs within Enterprise Digital & Analytics, with her team based in Bangalore and New York. In this role, she leads the charter to build and drive state-of-the-art AI capabilities and solutions to solve high-impact and complex business problems for the enterprise. Madhurima is a flagbearer of Inclusion & Diversity for Amex and is passionate about creating a culture of inclusiveness and empowerment for all her colleagues. Topics explored included: • Can you share more about the course of your career at Amex and your progression to this current role? • What are you currently working on at Amex AI Labs and how does Amex use AI & ML? • What does a typical working day look like for you? • How has COVID-19 changed the dynamic of work for you? • What have been the most important things for you in your career progression? • How have you created a culture of inclusiveness at Amex? Can you tell us more about your work in this area and what it means to you? • What are your thoughts on the challenges faced by women as AI practitioners? Read the transcript here. View all our upcoming Women in AI events here. Inspired to hear more? Recap interviews and presentations from inspiring Women in AI on the AI Library here. You can connect with Madhurima via LinkedIn.
This week's podcast is a discussion with Diana Murgulet who is a Data Scientist at QuantumBlack. QuantumBlack is an advanced analytics firm operating at the intersection of strategy, technology and design to improve performance outcomes for organisations. Diana has a background in Computer Science and Machine Learning. She is passionate about education, AI for Social Good and making tech more inclusive. Topics explored included: • Can you share more about your route getting into AI? • What was your experience of starting out your career in your first roles, and your initial job hunt? • Have you come across imposter syndrome and what advice would you give to anyone struggling with it? • How important is giving back to the community, especially mentoring women at the beginning of their career in AI? • Have role-models been a vital part of your career? • What does a typical working day look like for you? And which industries and topics are you currently focusing on? • What are your thoughts on the challenges faced by women as AI practitioners? • How has COVID-19 changed the dynamic of work for you? Read the transcript here. View all our upcoming Women in AI events here. You can connect with Diana via LinkedIn.
This week's guest is Rosana de Oliveira Gomes, Lead Machine Learning Engineer at Omdena. Omdena is a global platform bridging mission-driven organizations with AI engineers, data scientists, and experts from diverse backgrounds to solve real-world problems. Rosana started her career as an Astrophysicist but is now transitioning into Artificial Intelligence for social good, applying her knowledge into the nonprofit and humanitarian sector, on projects including AI for cyclone response and preventing online violence against children. Topics explored included: * What does AI for social impact mean to you? * What are some of the most urgent social challenges faced by humanity that AI can help tackle? * Can you share more about your story on transitioning from Astrophysics into the AI for social good space? * What skills can be transferred from academia into the field of AI? * What are the key challenges you have come across when practising AI for social good? * How can enterprises and companies best engage in AI for social good? * How do you think COVID-19 has impacted the AI for good space? * What advice would you give to someone looking to change their career? * What are your thoughts on the challenges faced by women as AI practitioners? Read the transcript here. Explore hours of AI for Good content on our AI Library. You can connect with Rosana via LinkedIn.
This week I had the pleasure of chatting with Paige Dickie, Head of AI at Layer 6. Paige began her career in management consulting, working across topics from data strategy, to digital transformation. More recently, Paige worked at the Vector Institute for Artificial Intelligence, where she leads initiatives with Canada's largest financial institutions, consulting companies, regulators, and government agencies, before joining TD's Layer 6 AI earlier this year. At Layer 6, Paige is globally responsible for the end-to-end workflow and lifecycle of all use-cases across the bank. In this episode, hear more about Paige's journey into AI, the role models that have helped along the way, as well as her advice for people starting in the field. Topics explored include: - The Exciting Potential for AI in the Future - Canada's Contribution to AI, the Institutes and Its Influential Thinkers - A Day in the Life for Paige at Layer 6 - The Integration Between Layer 6 and the Bank - Advice for Beginners Entering Their AI Career - AI for Social Good & Ethics, and What Social Benefits Can It Enable? - Tips for Women in AI and Role Models Read the transcript here. If you're keen to boost your AI knowledge, sign up for a free trial of our AI Library, with over 500 hours of AI video content available. You can connect with Paige via LinkedIn.
This week I had the pleasure of chatting with Valeria Cortez, Senior Data Scientist at Monzo Until recently, she worked on the development of Machine Learning solutions at Lloyds Banking Group. During this time, she focused on building tools and processes to detect and mitigate bias in Machine Learning models. Valeria is a strong advocate of ethics and responsibility in AI as well as bringing more diversity into tech teams. In September 2020, Valeria will be presenting a talk at the upcoming AI in Finance Virtual Summit, on her recent work in ML applications in banking. It was fantastic to hear more about Valeria's journey into AI, her recent move from old to new banking, and the challenges of bringing more diversity into tech teams. You can connect with Valeria via LinkedIn and follow her on twitter @ValeriaCortezVD.