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/

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 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.