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.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Robot Talk Episode 156 – Rugged robots for dangerous missions, with Gavin Kenneally

  15 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Gavin Kenneally from Ghost Robotics about robot dogs for defence, security, and public safety.

Developing active and flexible microrobots

  13 May 2026
This class of robots opens up possibilities for biomedical applications.

How to teach the same skill to different robots

  11 May 2026
A new framework to teach a skill to robots with different mechanical designs, allowing them to carry out the same task without rewriting code for each.

Robot Talk Episode 155 – Making aerial robots smarter, with Melissa Greeff

  08 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Melissa Greeff from Queen's University about autonomous navigation and learning for drones.

New understanding of insect flight points way to stable flapping-wing robots

  07 May 2026
The way bugs and birds flap their wings may look effortless, but the dynamics that keep them aloft are dizzyingly complex and difficult to quantify.

Robotically assembled building blocks could make construction more efficient and sustainable

  05 May 2026
Research suggests constructing a simple building from interlocking subunits should be mechanically feasible and have a much smaller carbon footprint.

Robot Talk Episode 154 – Visual navigation in insects and robots, with Andrew Philippides

  01 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Andrew Philippides from the University of Sussex about what we can learn from ants and bees to improve robot navigation.

Ultralightweight sonar plus AI lets tiny drones navigate like bats

  29 Apr 2026
Researchers develop ultrasound-based perception system inspired by bat echolocation.



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence