The Data Lab Community Meetup for Women in Data & AI, hosted by Alison Orr, Director of Marketing & Communications for The Data Lab, brought together a dynamic and diverse group of individuals passionate about advancing women in the fields of data, AI, and technology.
The event provided a platform for attendees to connect, share experiences, and explore opportunities to drive positive change. With a hybrid format that combined in-person engagement at The Bayes Centre in Edinburgh and live-streaming on YouTube (thanks to our friends at Product Forge), this event proved to be a resounding success.
We were joined by an enthusiastic group of women (and even a few men), many of whom were already part of the Women in Data & AI Community group. The Data Lab Community team were sure to provide free pizza and drinks to help re-charge attendees on this unusually hot evening. Post-event, the opportunity to network, learn, and mentor encouraged a new wave of online community members.
Couldn’t make it this time? Here’s a quick recap …
Panel discussion: Women leading the way in STEM
The panel discussion was a highlight of the event, featuring accomplished women in the data and AI space. Let’s meet our inspiring panellists:
Kate Farrell works on the Data Education in Schools project developing data science and data literacy lessons, resources and professional learning for primary and secondary schools in Scotland. She has also worked with the Scottish Qualifications Authority (SQA) to create a national secondary school qualification in Data Science. Previously she advised on the new Computing Science outcomes in Scotland’s national curriculum, wrote a guide for primary and early years on teaching the new CS outcomes (available free at TeachCS.Scot) and developed new badge activities in computational thinking with Girl Guiding UK.
Ivona Vickovic is a Technical Manager for Image Analysis Group, Canon Medical Research Europe, as well as an experienced engineer with 17+ years in the tech industry. She started out in semiconductor design, progressed via HW chip lead, design automation and SW product ownership roles to technical leadership in medical tech and AI. She’s currently a group manager for cross-functional R&D teams working on imaging AI and image analysis algorithms at Canon Medical. She’s passionate about tech for good, research and product delivery, knowledge sharing, and working with cross-functional and diverse teams.
Alessandra Fassio is the Senior Data Ethicist at the Ministry of Justice UK, where she leads on the department’s data ethics strategy. A core component of this role is to ensure that teams developing data products have the skills, resources, and processes to critically assess the wider societal impact of their technology and data.
Prior to joining the Ministry of Justice, Alessandra worked at the Data for Children Collaborative, where she was responsible for designing their Responsible Innovation framework, compiling various ethical, safeguarding and participation tools to help project teams use data safely and ethically. She has also participated in various Scottish Government data ethics initiatives, including the Data & Intelligence Network ethics framework and the independent report: ‘Building trust in the digital era.’
Emily Seward is Head of Data Applications at Intelligent Growth Solutions (IGS), having joined the business at the end of 2021. She leads a multi-disciplinary data applications team comprised of data scientists, data engineers and visualisation experts who use advanced data analysis techniques including artificial intelligence and machine learning to build applications designed to enhance the experience of growing in an IGS Growth Tower for the business’ customers.
Questions that our Women in Data & AI panel addressed:
- Emily – You are in a senior role. Can you tell us about any challenges you have faced as a woman in a male-dominated sector and how you dealt with these? Have you encountered resistance along the way?
- Kate – what advice would you give to women starting (or new to) their career to achieve their goals and the best places to seek support? If you can draw on some of your own experience, that would be great. We are interested in whether you have noticed the landscape has changed over time.
- Ivona – In your experience of the private sector, how do you think organisations perform in terms of enabling women to grow in STEM/data careers? Is this something you have seen change and improve? Can you talk about your own experience?
- Alex – would you say you have experienced barriers in your career so far, and have you noticed any difference coming from humanities into the data world? If you have, what would you relate this to?
- Ivona – You are a successful mentor in The Data Lab Community. Would you say having a mentor/role model is important, and is it something you have relied on in the past?
- Kate – you are at the frontline, engaging young people about data literacy and computing. How positive do you feel about the level of girls and women entering the tech sector? And what more do you think could be done?
- Alex – we have a quote from you on our Community ‘Now more than ever, diversity of skills and experience is going to be critical in helping to forge socially and ethically responsible technology’. Can you tell us your view on this, why it’s important and where you see your role in it?
- Emily – can you tell us how your organisation is structured regarding gender split and culture? You have talked about structuring to team in a ‘different way’. How do you go about this, and why is it important?
Engaging discussions on event topics
Following the panel discussions, in-person attendees had the opportunity to break into groups for engaging discussions and networking sessions. The “You Suggest The Topic” segment allowed participants to contribute their ideas and drive conversations around key areas of interest. Some of the selected topics included:
- AI Start-ups in Edinburgh: Exploring the thriving AI start-up scene in Edinburgh and uncovering opportunities for collaboration and growth.
- Misogyny in Practice: Addressing challenges women face in the industry and discussing ways to tackle misogyny, promote inclusivity, and foster a supportive environment.
- Diverse Backgrounds in Data Science: Embracing and celebrating the value of diverse backgrounds and experiences in data science.
- Early Career Advice: Sharing insights and guidance for those starting their careers in data and AI, providing mentorship and support for aspiring professionals.
- Preparing for AI: Discussing the impact of AI on various industries and exploring ways to prepare for the future of work.
- Breaking Through Buzzwords: Demystifying complex terminology and buzzwords in the data and AI space, making them accessible and understandable for all.
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The Data Lab Community welcomes attendees from all backgrounds and abilities.
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