Archive for the ‘#AIinEd’ Category

Data Driven Science

September 29th, 2020 by Graham Attwell

This diagram is from a tweet by  Data Driven Science (@DrivenScience).

Artificial Intelligence they say, is the broad discipline of creating intelligent machines.

Machine Learning refers to systems that can learn from experience.

Deep Learning refers to experience on large data sets.

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The State of Data 2020

September 28th, 2020 by Graham Attwell
social media, media, board

geralt (CC0), Pixabay

One result of the Covid 19 pandemic is it seems like every day now there are free events. This week is no exception and this conference looks great. I can’t make all of it – too many other meetings but I hope to dip in and out (another advantage of online conferences).

On Tuesday September 29 and Wednesday September 30, 2020 the State of Data event will bring together researchers, practitioners, and anyone with an interest in why data matters in state education in England.

You can choose to register if you want to use the calendar functionality and accept the privacy terms of Hopin, to see the events as they come live. Or simply watch in your own time without registering, after the event, via the links below.

Between algorithmic fairness in exam moderation and the rush to remote learning in response to the COVID-19 pandemic, 2020 has raised questions on children’s digital rights like never before in England’s education system. defenddigitalme is a call to action.

The conference has a vision of a rights’ respecting environment in the state education sector in England. We want to help build the future of safe, fair and transparent use of data across the public sector. This event will coincide with the launch of their report The State of Data 2020: mapping the data landscape in England’s state education system.

There is a range of content and discussion for practitioners in education and data protection, senior leadership and DPOs, local authority staff, developers, vendors and the edTech community, academics and activists, policy advisors and politicians —they say they want to create opportunities for questions and answers across silos. As the conference web site says: “We need to start a conversation about changing policy and practice when it comes to children’s data rights in education.”

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Racial bias in algorithms

September 25th, 2020 by Graham Attwell

From the UK Open Data Institute’s Week in Data newsletter

This week, Twitter apologised for racial bias within its image-cropping algorithm. The feature is designed to automatically crop images to highlight focal points – including faces. But, Twitter users discovered that, in practice, white faces were focused on, and black faces were cropped out. And, Twitter isn’t the only platform struggling with its algorithm – YouTube has also announced plans to bring back higher levels of human moderation for removing content, after its AI-centred approach resulted in over-censorship, with videos being removed at far higher rates than with human moderators.

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Accountability and algorithmic systems

September 3rd, 2020 by Graham Attwell
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geralt (CC0), Pixabay

There seems to be a growing awareness of the use and problems with algorithms – at least in the UK with what Boris Johnson called “a rogue algorithm” caused chaos in students exam results. It is becoming very apparent that there needs to be far more transparency in what algorithms are being designed to do.

Writing in Social Europe says “Algorithmic systems are a new front line for unions as well as a challenge to workers’ rights to autonomy.” She draws attention to the increasing surveillance and monitoring of workers at home or in the workplace. She says strong trade union responses are immediately required to balance out the power asymmetry between bosses and workers and to safeguard workers’ privacy and human rights. She also says that improvements to collective agreements as well as to regulatory environments are urgently needed.

Perhaps her most important argument is about the use of algorithms:

Shop stewards must be party to the ex-ante and, importantly, the ex-post evaluations of an algorithmic system. Is it fulfilling its purpose? Is it biased? If so, how can the parties mitigate this bias? What are the negotiated trade-offs? Is the system in compliance with laws and regulations? Both the predicted and realised outcomes must be logged for future reference. This model will serve to hold management accountable for the use of algorithmic systems and the steps they will take to reduce or, better, eradicate bias and discrimination.

Christina Colclough believes the governance of algorithmic systems will require new structures, union capacity-building and management transparency.I can’t disagree with that. But also what is needed is a greater understanding of the use of AI and algorithms – for good and for bad. This means an education campaign – in trade unions but also for the wider public to ensure that developments are for the good and not just another step in the progress of Surveillance Capitalism.

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Algorithmic bias explained

August 27th, 2020 by Graham Attwell

Yesterday, UK Prime Minister blamed last weeks fiasco with public examinations on a “mutant algorithm”. This video by the  Institute for Public Policy Research provides a more rational view on why algorithms can go wrong. Algorithms, they say, risk magnifying human bias and error on an unprecedented scale. Rachel Statham explains how they work and why we have to ensure they don’t perpetuate historic forms of discrimination.

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New report on Artificial Intelligence in Vocational Education and Training

July 31st, 2020 by Angela Rees

The Taccle AI project has launched it’s 74 page report exploring the use of AI in policy, process and practice in VET. For VET teachers and trainers, there are many possible uses of AI including new opportunities for adapting learning content based on student’s needs, new processes for assessment, analysing possible bottlenecks in learners’ domain understanding and…

PlayPlay
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Digitalisation, Artificial Intelligence and Vocational Occupations and Skills

July 27th, 2020 by Graham Attwell

geralt (CC0), Pixabay

The Taccle AI project on Artificial Intelligence and Vocational Education and Training, has published a preprint  version of a paper which has been submitted of publication to the VET network of the European Research Association.

The paper, entitled  Digitalisation, Artificial Intelligence and Vocational Occupations and Skills: What are the needs for training Teachers and Trainers, seeks to explore the impact AI and automation have on vocational occupations and skills and to examine what that means for teachers and trainers in VET. It looks at how AI can be used to shape learning and teaching processes, through for example, digital assistants which support teachers. It also focuses on the transformative power of AI that promises profound changes in employment and work tasks. The paper is based on research being undertaken through the EU Erasmus+ Taccle AI project. It presents the results of an extensive literature review and of interviews with VET managers, teachers and AI experts in five countries. It asks whether machines will complement or replace humans in the workplace before going to look at developments in using AI for teaching and learning in VET. Finally, it proposes extensions to the EU DigiCompEdu Framework for training teachers and trainers in using technology.

The paper can be downloaded here.

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July 22nd, 2020 by Graham Attwell

As part  of the Taccle AI project, around the impact of AI on vocational education and training in Europe, we have undertaken interviews with managers, teachers, trainers and developers in five European countries (the report of the interviews, and of an accompanying literature review, will be published next week).  One of the interviews I made was with Aftab Hussein, the ILT manager at Bolton College in the north west  of Engand. Aftab describes himself on Twitter (@Aftab_Hussein) as “exploring the use of campus digital assistants and the computer assisted assessment of open-ended question.”

Ada, Bolton College’s campus digital assistant has been supporting student enquiries about college services and their studies since April 2017.In September 2020, the college is launching a new crowdsourcing project which seeks to teach Ada about subject topics. They are seeking the support of teachers to teach Ada about their subjects.

According to Aftab “Teachers will be able to set up questions that students typically ask about subject topics and they will have the opportunity to compose answers against each of these questions. No coding experience is required to set up questions and answers.Students of all ages will have access to a website where they will be able to select a subject chatbot and ask it questions. Ada will respond with answers that incorporate the use of text, images, links to resources and embedded videos.

The service will be free to use by teachers and students.”

If you are interested in supporting the project complete the online Google form.

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AI and Young People

July 17th, 2020 by Graham Attwell

Last December, the Youth Department of the Council of Europe organised a seminar on Artificial Intelligence and its Impact on Young People. The aim of the seminar was to explore the issues, role and possible contributions of the youth sector in an effort to ensure that AI is responsibly used in democratic societies and that young people have a say about matters that concern their present and future. The seminar looked, among other things, into three dimensions of AI”

  • AI and democratic youth participation (including young people’s trust/interest in democracy)
  • AI and young people’s access to rights (including social rights)
  • AI and youth policy and youth work

According to the report of the seminar, the programme enabled the participants to put together their experience and knowledge in proposing answers to the following questions:

  • What are the impacts of on young people and how can young people benefit from it?
  • How can the youth sector make use of the capacities of to enhance the potential of youth work and youth policy provisions for the benefit of young people?
  • How to inform and “educate” young people about the potential benefits and risks of AI, notably in relation to young people’s human rights and democratic participation and the need to involve all young people in the process?
  • How does AI influence young people’s access to rights?
  • What should the youth sector of the Council of Europe, through the use of its various instruments and partners, do about AI in the future?

Not only is there a written report of the seminar but also an excellent illustrated report. Sadly it is not in a format that  can be embedded, but  it is well worth going to the Council of Europe’s web page on AI and scrolling to the bottom to see the report.

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European Union, AI and data strategy

July 9th, 2020 by Graham Attwell
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geralt (CC0), Pixabay

is the rapporteur for the industry committe for European Parliament’s own-initiative  on data strategy and  a standing rapporteur on the World Trade Organization e-commerce negotiations in the European Parliament’s international trade committee.

Writing in Social Europe she says:

Building a human-centric data economy and human-centric artificial intelligence starts from the user. First, we need trust. We need to demystify the data economy and AI: people tend to avoid, resist or even fear developments they do not fully understand.

Education plays a crucial role in shaping this understanding and in making digitalisation inclusive. Although better services—such as services used remotely—make life easier also outside cities, the benefits of digitalisation have so far mostly accrued to an educated fragment of citizens in urban metropoles and one of the biggest obstacles to the digital shift is lack of awareness of new possibilities and skills.

Kampula-Natri draws attention to the Finnish-developed, free online course, ‘Elements of AI’. This started as a course for students in the University of Helsinki but has extended  its reach to over 1 per cent of Finnish citizens.

Kampula-Natri points out that in the Nordic countries, the majority of participants on the ‘Elements of AI’ course are female and in the rest of the world the proportion exceeds 40 per cent—more than three times as high as the average ratio of women working in the technology sector. She says that after the course had been running in Finland for a while, the number of women applying to study computer science in the University of Helsinki increased by 80 per cent.

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    Racial bias in algorithms

    From the UK Open Data Institute’s Week in Data newsletter

    This week, Twitter apologised for racial bias within its image-cropping algorithm. The feature is designed to automatically crop images to highlight focal points – including faces. But, Twitter users discovered that, in practice, white faces were focused on, and black faces were cropped out. And, Twitter isn’t the only platform struggling with its algorithm – YouTube has also announced plans to bring back higher levels of human moderation for removing content, after its AI-centred approach resulted in over-censorship, with videos being removed at far higher rates than with human moderators.

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    Gap between rich and poor university students widest for 12 years

    Via The Canary.

    The gap between poor students and their more affluent peers attending university has widened to its largest point for 12 years, according to data published by the Department for Education (DfE).

    Better-off pupils are significantly more likely to go to university than their more disadvantaged peers. And the gap between the two groups – 18.8 percentage points – is the widest it’s been since 2006/07.

    The latest statistics show that 26.3% of pupils eligible for FSMs went on to university in 2018/19, compared with 45.1% of those who did not receive free meals. Only 12.7% of white British males who were eligible for FSMs went to university by the age of 19. The progression rate has fallen slightly for the first time since 2011/12, according to the DfE analysis.

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    Quality Training

    From Raconteur. A recent report by global learning consultancy Kineo examined the learning intentions of 8,000 employees across 13 different industries. It found a huge gap between the quality of training offered and the needs of employees. Of those surveyed, 85 per cent said they , with only 16 per cent of employees finding the learning programmes offered by their employers effective.

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    News from 1994

    This is from a Tweet. In 1994 Stephen Heppell wrote in something called SCET” “Teachers are fundamental to this. They are professionals of considerable calibre. They are skilled at observing their students’ capability and progressing it. They are creative and imaginative but the curriculum must give them space and opportunity to explore the new potential for learning that technology offers.” Nothing changes!

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