Tech Ethics Bristol Event #4 – AI ethics best practices and the future of innovation

ADLIB are pleased to be sponsoring the first in person event for Tech Ethics Bristol – AI ethics best practices and the future of innovation.

Ethical considerations and awareness of the unintended consequences of emerging technologies are transforming the way we relate to each other and with the companies offering these services.

Trust and transparency have become essential values for any business working with technology, and in this special event, we will be sharing some examples of best practices and perspectives from organizations working in AI ethics.

This first in-person event will be on Wednesday 13th October from 4 pm at the Engine Shed for an evening of discussions and practical insights with experts from industry and academia.

This event is part of The Bristol Technology Festival 2021.

RSVP

 

Presentations:

1. Adopting an ESG strategy for ethical organisations. Ethics Grade.

Environmental Social and Governance (ESG) has become a priority for organisations around the world. However, an area of ESG which is often overlooked is Digital Responsibility, and more specifically, AI Governance. 

In this presentation, Will Lllewelyn will talk about the importance of recognising AI Governance as an ESG issue and what companies can do to manage AI systems safely and ethically.

Speaker: William Llewelyn

William is a Data Analyst by trade with an interest in innovation, technology and ESG. He works in the asset management industry and is the Co-founder of EthicsGrade, an ESG data company that looks specifically at how companies manage their technology -Artificial Intelligence- and whether they do so ethically.

2. The Data Hazard Labels Project. Jean Golding Institute. University of Bristol.

In this talk, Nina and Natalie from Jean Golding Institute will be presenting the initial results of a project to create a series of Data Hazard labels, which aim to help innovators and researchers reflect on and communicate the potential ethical implications of their data science work to wider audiences.

Speakers:  Natalie Thurlby

Natalie is a Data Scientist working at the Jean Golding Institute, the University of Bristol’s research institute for data science and data-intensive research. She supports data science research in the university on a range of projects from digital humanities to health sciences.

Nina Di Cara 

Nina Di Cara is a PhD student at the University of Bristol. She studies data science for mental health, and before starting her PhD was trained as a social worker. 

3. Ethical AI in practice. LV Insurance.

In order for businesses to minimize risk when deploying machine learning models, they must have a rigorous process of model governance & risk analysis which emphasises ethical considerations to avoid potential discrimination or similar negative results.

LV= have a mature data science team of over 40 and are leading the way when it comes to best practice when implementing machine learning into their systems and processes.

In this talk, Venura will give an overview of the areas businesses should consider when it comes to embedding AI ethics into their governance, working practices and culture.

Speaker : Venura Perera 

Venura is the Director of Data Science Innovation & Proposition at LV= General Insurance and is also a Visiting Research Fellow at the University of Bristol. 

He is part of the Data Science Team for LV= in Bristol which also works closely on novel research with the University of Bristol.

He has a PhD In Computational & System Biology from the University of Exeter and has worked in commercial  Data Science roles for the past 7 years and well as being an active member of the data science research community.

Tech Ethics Bristol

Wednesday 13th October

4 to 6:30 pm

Engine Shed, Bristol

For free tickets please sign up for the event HERE

Tech Ethics Bristol is organised by Collective Intelligence.

https://www.collective-intelligence.co.uk/

And sponsored by Adlib.

https://www.adlib-recruitment.co.uk/