Robohub.org
 

UK Royal Society wants to hear your thoughts on machine learning

by
23 December 2015



share this:

How is Robohub doing? Take our annual reader survey!
The UK Royal Society would like to hear your thoughts on machine learning – you are invited to answer some or all of the questions set out in a Call for Evidence here. The closing date for evidence is 3 January.

Machine Learning
Many services that we use every day rely on machine learning. Machine learning is used in internet search engines, email filters to sort out spam, websites to make personalised recommendations, banking software to detect unusual transactions, and lots of apps on our phones such as voice recognition.

Many services that we use every day rely on machine learning.

The technology has many more potential applications, some with higher stakes than others. Future developments could support the UK economy and will have a significant impact upon society. For example, machine learning could provide us with readily available ‘personal assistants’ to help manage our lives, it could dramatically improve the transport system through the use of autonomous vehicles; and the healthcare system, by improving disease diagnoses or personalising treatment. Machine learning could also be used for security applications, such as analysing email communications or internet usage. The implications of these and other applications of the technology need to be considered now and action taken to ensure uses will be beneficial to society.

What is the Royal Society project about?
There are both opportunities and challenges around this transformative technology and it raises social, legal, and ethical questions. This is why the Royal Society is starting a project on machine learning, aiming to stimulate a debate, to increase awareness and demonstrate the potential of machine learning and highlight the opportunities and challenges it presents. In the course of the project we will engage with policymakers, academia, industry and the wider public.

There are both opportunities and challenges around this transformative technology

The project will focus on current and near-term (5-10 years) applications of machine learning. It will have a strong public engagement element, and a variety of resources will be produced over the course of the project. The project scope was developed by a Core Group of experts who met over the summer 2015.

Who will inform this project?
This Royal Society project will be led by a Working Group involving a range of expertise.

You can also have a say.

Have your say
You can also have a say. This Royal Society project will involve a public dialogue exercise and ensure that public views inform policy development. You can start by responding to some of the questions in our Call for Evidence.



tags: , ,


Aleks Berditchevskaia works in the new and emerging technologies team of the Science Policy Centre at the Royal Society.
Aleks Berditchevskaia works in the new and emerging technologies team of the Science Policy Centre at the Royal Society.





Related posts :



Robot Talk Episode 100 – Mini Rai

In the latest episode of the Robot Talk podcast, Claire chatted to Mini Rai from Orbit Rise about orbital and planetary robots.
29 November 2024, by

Robot Talk Episode 99 – Joe Wolfel

In the latest episode of the Robot Talk podcast, Claire chatted to Joe Wolfel from Terradepth about autonomous submersible robots for collecting ocean data.
22 November 2024, by

Robot Talk Episode 98 – Gabriella Pizzuto

In the latest episode of the Robot Talk podcast, Claire chatted to Gabriella Pizzuto from the University of Liverpool about intelligent robotic manipulators for laboratory automation.
15 November 2024, by

Online hands-on science communication training – sign up here!

Find out how to communicate about your work with experts from Robohub, AIhub, and IEEE Spectrum.
13 November 2024, by

Robot Talk Episode 97 – Pratap Tokekar

In the latest episode of the Robot Talk podcast, Claire chatted to Pratap Tokekar from the University of Maryland about how teams of robots with different capabilities can work together.
08 November 2024, by

Robot Talk Episode 96 – Maria Elena Giannaccini

In the latest episode of the Robot Talk podcast, Claire chatted to Maria Elena Giannaccini from the University of Aberdeen about soft and bioinspired robotics for healthcare and beyond.
01 November 2024, by





Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association