Final Call December AI-2026: Cambridge, UK :: June: Virtual seminar on 'A Future with AI Agents'

FINAL CALL FOR PAPERS AND POSTERS

The proceedings of the AI-20xx conference series are now published by Springer in Lecture Notes in Artificial Intelligence (LNAI), a sub-series of the distinguished Lecture Notes in Computer Science (LNCS) series of conference proceedings.

AI-2026: Cambridge, UK, December 15th-17th 2026

Organised by BCS SGAI: The British Computer Society Specialist Group on Artificial Intelligence (a EurAi Member Society).The leading series of UK-based international conferences on Artificial Intelligence and one of the longest running AI conference series in Europe.

CALL FOR CONTRIBUTIONS

http://www.bcs-sgai.org/ai2026/

AI-2026 is the forty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. The scope of the conference comprises the whole range of AI technologies and application areas. AI-2026 reviews recent technical advances in AI technologies and shows how these advances have been applied to solve business problems. Key features are:

• Papers will be published by Springer in the Lecture Notes in Artificial Intelligence (LNAI) subseries of the popular Lecture Notes in Computer Science (LNCS) series (
• Papers are invited in two streams. The Technical Stream presents the best of recent developments in AI, covering a wide range of technical areas. The Application Stream is the largest annual showcase in Europe of real applications using AI technology.
• It is expected that the best papers will be reprinted in expanded form in an international journal.
• A mixture of full papers (maximum 14 A4 pages) presented orally and short papers (maximum 6 A4 pages) presented as posters. Papers of both kinds will be included in the proceedings.
• Prizes for best paper and best student paper in each stream and best presented short/poster paper.
• Invited keynote lectures.
• The first day comprises tutorials and workshops to provide greater depth in selected topics. (Separate one-day registration for this day is also available.
• A panel session or a debate on a topical subject.
• An 'AI Open Mic' session to allow delegates to have their say about any aspect of AI.
• In addition to the formal sessions, the conference programme includes a welcome reception and a Gala Dinner.

AI-2026 offers a valuable opportunity to keep up to date with developments in AI and to share experiences in the practical issues of developing AI systems.

More details ... 

:::: PLUS :::::

-------- Virtual Meeting seminar on A Future with AI Agents --------

The next in our series of free evening virtual seminars will be on Wednesday June 10th from 6 p.m. to 7.30 p.m. (UK time). The topic will be A Future with AI Agents.

 

Humans are becoming the minority online with bots generating almost 50% of all internet traffic. The World Economic Forum recognised that the advancement of agentic AI is obvious and the agent-driven economy is here. The global AI agents market is growing from a $5.4 billion market in 2024 to $236 billion by 2034. Come along and find out about some technical foundations of agentic systems and how to build a minimal AI agent from scratch.

 

The speakers will be

Anirban Lahiri (Arndit Ltd., Cambridge, United Kingdom) on Agentic AI: A Friend or Foe'
Dr Mercedes Arguello Casteleiro (SGAI) on 'AI Agents 101'

The virtual seminar series is free and open to all. For further details and for the zoom link to use go to https://bcs-sgai.org/seminars/2026-06-10/.

 

Details of future SGAI events will be placed on the website at https://bcs-sgai.org as they become available. To register to be sent information about future SGAI events by email go to https://www.bcs-sgai.org/register/.

 

Max Bramer

Chair, BCS SGAI

----------------------------------------------------

Chair, British Computer Society Specialist Group on Artificial Intelligence

Emeritus Professor, School of Computing, University of Portsmouth, UK
http://www.maxbramer.org

 

My source: AI-SGES list

ERCIM News No. 143 Special theme: "AI for Science"

 
Dear ERCIM News reader,

ERCIM News 143 is now online! The articles in this special theme show that AI is no longer a peripheral tool in science, but a central part of research practice across disciplines. AI for Science is reshaping how research is organised, understood, and conducted, while also raising important questions about trust, transparency, energy use, and the evolving role of human expertise.

Read the January 2026 Issue

This issue in PDF

This special theme was coordinated by our guest editors Edina Nemeth (SZTAKI) and Alexandre Termier (University of Rennes – Inria/IRISA).

Next Issue

No. 144 – April 2026
Special Theme: Open Science Experiences and Prospects
Call for Contributions

Announcements in this issue

• Dagstuhl Seminars & Workshops | Call for Proposals
• Fraunhofer–Bessel Research Award | Call for Nominations
• 2nd AIOTI Workshop on Semantic Interoperability for Digital Twins | Call for Participation
• Welcome to the 45th SAFECOMP 2026 | Call for Papers
• FMICS 2026: 31st International Conference on Formal Methods for Industrial Critical Systems | Call for Papers
• SAFECOMP 2026 45th International Conference on Computer Safety, Reliability and Security | Call for Workshop Proposals
• 21st International EWICS / ERCIM Workshop on Dependable Smart Embedded Cyber-Physical Systems and Systems-of-Systems (DECSoS 2026) | Pre-Announcement
• ERCIM “Alain Bensoussan” Fellowship | Next application deadline: 31 March 2026

My source:
Peter Kunz ERCIM https://www.ercim.eu https://ercim-news.ercim.eu

ii Learn your lines and the hyperplanes will follow

With these lines, partitions, axes and domains in mind, when a clinical practitioner is presented with a new person, whether as a patient, client, or carer ... they can, using Hodges' model (and other tools!) approach their assessment in an open and receptive manner.

This means that the information provided by the 'patient' can be readily fielded, captured whatever the context and situation.

As noted previously, my study of Hodges' model began in the late 1980s. Application in my work as a community mental health nurse, with an interest in informatics followed quite naturally(?). Primed as I was, for various reasons to carry this forward, I also carried a mathematical learning disability. At the risk of getting bogged down in my thought, use and approach to Hodges' model I need a challenge.

Mathematics is the challenge for me. It's fascinating how we have in-built 'calculators' that can help us catch a ball, and judge fairly well where to throw a ball for interception. There seems then to be an informal or naïve  mathematics, at work unconsciously. Does the same apply to Hodges' model? If so, how can I isolate, and identify it?

• Is it represented somewhere, implicit in Hodges' model itself?
• Is it (once again) to be found in the user of the model?
• Is it (more likely, and obviously) a combination of these two?
• Or, is it a product of the system, or a series of systems? 

I was reminded of what is a Sober toy, several years ago:

Is Hodges' model a selection machine?

All four original purposes of Hodges' model:

1. Person-centred, integrated and holistic care;
2. To bridge the theory - practice gap;
3. To facilitate reflection and reflective practice;
4. To support curriculum development;

- are concerned with conjunction and choice, selection. So is life itself through distinction, difference, and differentiation.

Hodges' model is a selection machine, that is both fhuman and machine driven.

A clinician may obtain the referral information through an email, a history of previous contacts can be retrieved from a clinical information system; the context and purpose supporting access to the information.   

A whole series of blog posts describe the role of Hodges' model to help assure parity of esteem across mental and physical health. What does this mean in practice?

For the practitioner, they take selected data from the referral, a history - if available, an initial telephone contact, a conversation with a colleague who remembers the person re-referred and starts to populate Hodges' model. What are the psychological concepts that arise? What are the physical?

If a referral in whatever form, or a database record can be viewed as a bag-of-words, then Hodges' model is a collection of care concepts. Four bags then. Sets or classes. An experienced user of Hodges' model may position care concepts that throws attention on the INDIVIDUAL↔GROUP axis. Lying between the INTRA- INTERPERSONAL and SCIENCES domains, this axis (like all the others) earns its keep. There is work to be done that is also of interest in machine learning:

'A support vector machine (SVM) is a supervised machine learning algorithm that classifies data by finding an optimal line or hyperplane that maximizes the distance between each class in an N-dimensional space.

SVMs were developed in the 1990s by Vladimir N. Vapnik and his colleagues, and they published this work in a paper titled "Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing"¹ in 1995.' 

https://www.ibm.com/think/topics/support-vector-machine

Strange to think that perhaps the VERTICAL axis and others in Hodges' model are not precisely S-N-E-W in their bearing? There may also be several vectors at work in fact?

Image: c/o https://www.ibm.com/think/topics/support-vector-machine

The word 'naïve' has been bubbling away for a good-many years. A close colleague Silvana Bettiol, Univ. of Tasmania kindly read my draft on Hodges' model as a mathematical object, and mentioned the introduction points to Bayes theorem even if informally. Even in those initial 'clinical' encounters (and social meetings, that attend to empathy, rapport and engagement...) complex judgements are being made, beliefs tested, from what is often partial and disparate sources of information.

Checking other leads led to Frequentist and Bayesian Approaches

'Statistical inference is a series of methods used to make decisions and draw conclusions based on available data. There are two primary approaches for inference: Frequentist and Bayesian. Each framework relies on a different philosophical perspective on probability and modeling, leading to different techniques and interpretations. Each has its own strengths and drawbacks, so understanding the distinctions between them is vital for researchers, data scientists, and statisticians who aim to choose the most suitable approach for their specific analysis.'
https://www.statology.org/comparing-frequentist-and-bayesian-approaches/

More reading required and threads to run.

Earlier this week I posted re. Cromer's book -

Cromer, A. (1997) Connected Knowledge: Science, Philosophy, and Education, Oxford: Oxford University Press

Before passing the book on, p.198, Chapter 8 notes, #4:

'"Understanding" is a commonly used English word which has no precise meaning. It's sometimes taken to mean the ability to apply knowledge to new situations. In this sense, it is a very high-level skill. Benchmarks for Science Literacy says, "Learning to solve problems in a variety of subject-matter contexts, if supplemented on occasion by explicit reflection on that experience, may result in the development of a generalized problem-solving ability that can be applied in new contexts' (American Association for the Advancement of Science, 1993)." The key word here is "may." 'We really don't know how to help students develop a generalized problem-solving ability, or whether there is such an ability apart from mere knowledge of many different problem-solving strategies. Whatever the case, since we do know how to teach students to solve specific, problems. this should be the primary focus of science education' p.198.

Ack. IBM.

HC@AIxIA AI&Health May Seminar: 'Building Trustworthy AI for Health'

Dear Madam/Sir,

This is to officially announce the MAY 2025 seminar of the "AI & Health: Seminars 2025" series as hosted by HC@AIxIA, i.e., the "Artificial Intelligence for Healthcare" working group of the Italian Association for Artificial Intelligence.

*** Save the date: 12 MAY 2025. 3:30 CET ***

We hope you will attend and participate in the discussion on the relevant topics that will be presented and by our speakers. Feel free to share this with those potentially interested.

Link for participating: https://bit.ly/hc-2025-05 (PLEASE CHECK the site https://aixia.it/en/gruppi/hc/ for any changes or updates) - Please find some details below, and a poster attached.

== May 2025 seminar ==
2025 May 12 - 3:30PM CET

Prof. Barbara Di Camillo, Department of Information Engineering, University of Padova, Italy

Title: Building Trustworthy AI for Health: Robust and Generalizable Models with a Focus on Challenging Cases

Abstract: To make artificial intelligence useful in real clinical settings, it is crucial that AI tools follow the principles of trustworthy AI. This means ensuring the accuracy and reliability of the results, defining the areas where the results are valid, and making sure the predictions are understandable. This approach ensures that humans remain at the center of the decision-making process. BRAINTEASER (https://brainteaser.health/) is a data science project that uses artificial intelligence to help patients with amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS), along with their doctors. In the presentation, I will show how, during the development of the machine learning methods within the project, we took into account the robustness and generalizability of the model, and how we identified and characterized the subjects for whom making predictions is more challenging.

Short Bio: Barbara Di Camillo is full professor in computer science with the Department of Information Engineering, University of Padova. Her research activity is centered in the development and application of advanced modeling, data mining and machine learning methods for high-throughput biological data analysis in the field of Bioinformatics and Systems Biology. In particular, she has developed and applied different methods for robust biomarker discovery, predictive modeling and clustering of clinical data and next generation sequencing data. She has also a great expertise in the development and application of differential equation based models, Boolean and Bayesian Networks for modeling the relationships between the variables and the pathways along which they influence the disease progression.

Flyer: https://drive.google.com/open?id=15badJ0Nfj8lrA0gZdFc9aOGeR3pelms-&usp=drive_fs

====

Some notes
Serving as coordinators of the working group on AI for Healthcare of the Italian Association of Artificial Intelligence (AIxIA, see: https://aixia.it/en/gruppi/hc/), part of our commitment consists of fostering contamination and collaboration between AI researchers and experts and operators in Medicine and Healthcare; in particular, we aim to contribute in building a two-way road for informing healthcare operators about AI results and opportunities, while also raising awareness among AI researchers about challenges and problems in medicine and healthcare.
Therefore, the 2025 seminar series, in the trail of the 2024 edition, will feature a number of experts presenting research results, projects, best practices, ideas, and more to a mixed audience of AI researchers and healthcare operators.

Thank you for your interest in the AI & Health seminar series and the HC@AIxIA working group, and see you soon!

Sincerely,
Francesco Calimeri, Mauro Dragoni, Fabio Stella
(coordinators of the HC@AIxIA working group)

Living document - "Semantic Web: Past, Present, and Future"

Dear Semantic Web community

As the year ends, the question remains: How will the Semantic Web look in 2025?

Together with Katja Hose, Maria-Esther Vidal, Gerd Groener, and Petr Škoda, we contributed this year an article titled "Semantic Web: Past, Present, and Future", see

https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.3 to the new Diamond Open Access journal on Transactions on Graph Data and Knowledge (TGDK, https://tgdk.org/). This primer has been a living document for 13 years; see the link for details!

As many of us cannot resist checking emails over the break, I ask you to consider the question:
What is our future in 2025?

Many "classical" Semantic Web researchers have witnessed the rise of Linked Open Data, Freebase being bought by Google (largely seen as a big win), and the beginning and success of the Knowledge Graph era. Many of us have moved on to or added topics like graph representation learning, graph neural networks, language models, etc., to our research portfolio. So, how much of the classical topics are left? How much will come back? Should we work more on knowledge graph embeddings obeying OWL axioms? Shall we have federated queries not only over multiple data sources but also include hybrid queries using similarities in graph embeddings?

In the current 2024 version of the primer, we include the latest W3C standards developed by the Semantic Web community. But we also explain the journey from the famous Linked Data principles via Knowledge Graphs to the hot topic of machine learning on graphs!

*The article linked above is an invitation to contribute. Contact me if you are interested!* 

It will be updated from time to time. We like to receive your feedback, and perhaps you would like to contribute to a future version.

Best wishes and happy holidays,

Ansgar

PS: For 2025, there is a plan to update the German version of the article in an introductory textbook on artificial intelligence. It will add Shallow Graph Embeddings, Graph Neural Networks, and the interplay of Knowledge Graphs and Language Models. Once ready, I plan to ping this back to the English version.

My source:

Ansgar Scherp
From:mail AT ansgarscherp.net
To:semantic-web AT w3.org

4.3   3-12

'Domain Ontologies represent knowledge specific to a particular domain [48, 109]. Domain ontologies are used as external sources of background knowledge [48]. They can be built on foundational ontologies [110] or core ontologies [131], which provide precise structuring to the domain ontology and thus improve interoperability between different domain ontologies. Domain ontologies can be simple such as the FOAF ontology or the event ontology mentioned above, or very complex and extensive, having been developed by domain experts, such as the SNOMED medical ontology.' ...

3-13

'Foundational Ontologies have a very wide scope and can be reused in a wide variety of modeling scenarios [24]. They are therefore used for reference purposes [109] and aim to model the most general and generic concepts and relations that can be used to describe almost any aspect of our world [24, 109], such as objects and events. An example is the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) [24]. Such basic ontologies have a rich axiomatization that is important at the developmental stage of ontologies. They help ontology engineers to have a formal and internally consistent conceptualization of the world, which can be modeled and checked for consistency. For the use of foundational ontologies in a concrete application, i.e., during the runtime of an application, the rich axiomatization can often be removed and replaced by a more lightweight version of the foundational ontology.
 In contrast, domain ontologies are built specifically to allow automatic reasoning at runtime. Therefore, when designing and developing ontologies, completeness and complexity on the one hand must always be balanced with the efficiency of reasoning mechanisms on the other. In order to represent structured knowledge, such as the scenario depicted in Figure 1, interconnected ontologies are needed, which are spanned in a network over the Internet. For this purpose, the ontologies used must match and be aligned with each other.'

Health - See also 4.2 (A post in 2025 ...re. SKOS?).

ERCIM News No. 134 Special theme: "Explainable AI (XAI)"

Dear ERCIM News reader,

ERCIM NEWS 134

ERCIM News No. 134 has just been published. This issue's special theme dives into Explainable AI (XAI) – uncovering its application across healthcare, industry, ethics, climate change, and generative language models. Discover the significance of transparency and interpretability in complex ML models, offering insights into decision-making and building trust.

This special theme was coordinated by our guest editors by Manjunatha Veerappa (Fraunhofer IOSB) and Salvo Rinzivillo (CNR-ISTI).

Thank you for your interest in ERCIM News! Help us spread the word by forwarding this message to those who might find it interesting. We also appreciate your support on Twitter @ercim_news and other social media platforms. Let's keep the conversation going and share the latest updates together!




Includes:

Explainable AI in Health Care

16 Explaining Ensemble Models for Lung Ultrasound Classification

by Antonio Bruno, Giacomo Ignesti and Massimo Martinelli (CNR-ISTI)

18 A Governance and Assessment Model for Ethical Artificial Intelligence in Healthcare

by Luigi Briguglio, Francesca Morpurgo and Carmela Occhipinti (CyberEthics Lab.)

20 Current Challenges and Future Research Directions in Multimodal Explainable Artificial Intelligence

by Nikolaos Rodis, Christos Sardianos and Georgios Th. Papadopoulos (Harokopio University of Athens)

22 Predictive Model for Functional Outcome after Orthopaedic Surgery Using Machine Learning Methods

by Alexandre Lädermann (Hôpital de La Tour, Meyrin, Switzerland), Philippe Collin (American Hospital of Paris, France) and Patrick J. Denard (Oregon Shoulder Institute, Medford, Oregon, USA)

23 Unleashing the Power of Artificial Intelligence for Personalised Drug Design

by Michaela Areti Zervou, Effrosyni Doutsi, Panagiotis Tsakalides (University of Crete and ICS-FORTH)

Next issue:
No. 135,  October 2023
Special Theme: "Climate-Resilient Society".

Submissions are welcome! See call for contributions.

My source:

Peter Kunz                      	
ERCIM Office
2004, Route des Lucioles
BP93
F-06902 Sophia Antipolis Cedex

https://www.ercim.eu
https://ercim-news.ercim.eu 
--------------------------------
@ercim_news
http://twitter.com/ercim_news

join the ERCIM Linkedin Group
https://www.linkedin.com/groups/81390/

Artificial Intelligence and Data Science for Society and the Public Good: Technologies, Applications, and Governance

Dear CHAIN member,

CHAIN member Laura Brookes would like to draw your attention to the following free event.
Please pass on as appropriate. Thank you.

Artificial Intelligence and Data Science for Society and the Public Good:

Technologies, Applications, and Governance

2nd May 2023 - 3rd May 2023
Wivenhoe House Hotel

University of Essex, Park Road, Wivenhoe, Colchester, Essex, CO4 3SQ

Book your tickets now

Join us as we bring together the brightest minds in data science and AI to showcase the power of data in action for public good and business applications.

Two days of fascinating talks at the prestigious Wivenhoe House Hotel will include interactive workshops, case study presentations to share best practice and an opportunity to form new partnerships across academia, the public sector and industry for more high-impact projects moving forward.

This workshop aims to explore the development and deployment of AI and data science methods in government and the wider public sector, but also businesses and charities. This includes the use of such methods to support the development and implementation of policy and delivering improved services to citizens at the regional and national level, whilst we simultaneously tackle global challenges and the delivery of the sustainable development goals (SDGs).

This workshop is for those inspired to make a difference and for those ready to embrace the revolutionising potential of data science and AI to improve society for all. A cross/interdisciplinary workshop, this event is aimed at researchers, policymakers, practitioners and professionals already working in or interested in exploring this area.

Further information

Complimentary refreshments will be available on both workshop days including a networking lunch.

Guests are welcome to use the free onsite parking for the workshop. Delegates are also eligible for discounts on accommodation at the Wivenhoe House Hotel should they wish to stay overnight. To receive your discount code please contact me directly.

Further information about the event and full agenda can be found on Eventbrite:

https://AIandDataScienceforPublicGood.eventbrite.co.uk

We hope you can join us for this exciting workshop. Please feel free to contact if you wish to discuss any aspect further.

Equally, you are welcome to share this invitation with colleagues and those within your network. ‘

Laura Brookes

Outreach and Publicity Officer
ESRC Business and Local Government Data Research Centre
. . .

Regards,

Wendy Zhou
CHAIN Manager
[ I did attend, and spent the 1st May in Cambridge. PJ ].

ERCIM News No. 129 Special Theme: "Fighting Cybercrime"

 Dear ERCIM News reader,

Fighting Cybercrime is the special theme of ERCIM News No.129, just published at https://ercim-news.ercim.eu/

This issue's Special Theme contains many promising concepts, methods and solutions that contribute to the defense against and fight against cybercrime. This special theme has been coordinated by our guest editors Florian Skopik (AIT Austrian Institute of Technology) and Kyriakos Stefanidis  (ISI).

Thank you for your interest in ERCIM News. Feel free to forward this message to anyone who might be interested. We are also happy if you follow us and talk about us on twitter @ercim_news and other social media.

Next issue:
No. 130,  July 2022
Special Theme: "Assistive and Inclusive Technologies" (submissions welcome!)

---

ERCIM News is published quarterly by ERCIM, the European Research Consortium for Informatics and Mathematics. With the printed and online edition, ERCIM News reaches more than 10000 readers.

About ERCIM

ERCIM - the European Research Consortium for Informatics and Mathematics - aims to foster collaborative work within the European research community and to increase co-operation with European industry. Leading European research institutes are members of ERCIM. ERCIM is the European host of W3C.

https://www.ercim.eu/
https://twitter.com/ercim_news

Peter Kunz                      	
ERCIM Office
2004, Route des Lucioles
BP93
F-06902 Sophia Antipolis Cedex 

Call For Papers: Special Track on AI for Tackling Dis/Misinformation during Pandemics

Call For Papers: Special Track on AI for Tackling Dis/Misinformation during Pandemics In conjunction with the ACM International Conference on Information Technology for Social Good (GoodIT 2021)

The GoodIT conference is sponsored by ACM SIGCAS, the Association for
Computing Machinery's Special Interest Group on Computers & Society.

The conference focuses on the application of IT technologies to social good.

The Special Track on AI for Tackling Dis/Misinformation during Pandemics focuses on new data technologies based on artificial intelligence, data governance, machine learning, natural language
processing, and social network analysis to aid experts in analyzing large volumes of social media data in order to detect fake news, misinformation, and disinformation. A number of open challenges need
more investigation from the research community, such as recent trends in composing information disorder by combining false and real content, the mechanisms that drive fake content diffusion during pandemics, how to differentiate fake content from personal viewpoints, why people tend to believe fake content and make decisions based on it during pandemics, and what are the different motivations behind the dissemination of fake content. Fact-checking and claim verification are two important strategies that are worth incorporating in the automated tackling and curtailment of fake content during and after pandemics.

************ Key Dates ************

Papers Submission Due:      May 1, 2021

Authors Notifications:        June 22, 2021

Final Manuscript Due:        July 10, 2021

GoodIT 2021:                    September 09-11, 2021

************ Important Links ************

Special Track Website: https://aitdmp.conceptechint.net

Submission Link: https://goodit2021.hotcrp.com/

************ Submission Guidelines  ************

All submissions will be reviewed using a single-blind review process.

The identity of referees will not be revealed to authors, but authors can keep their names on the submitted papers, on figures, bibliography, etc.

Papers should not exceed 6 pages (US letter size) double column including figures, tables, and references in standard ACM format. Papers must be submitted electronically in printable PDF form.

Templates for the standard ACM format can be found here:

https://www.acm.org/publications/proceedings-template No changes to margins, spacing, or font sizes are allowed from those specified by the style files. Papers violating the formatting guidelines will be

returned without review.

ACM has partnered with Overleaf, a free cloud-based, collaborative authoring tool, to provide an ACM LaTeX authoring template. The ACM LaTeX template on Overleaf platform is available to all ACM authors at: www.overleaf.com/gallery/tagged/acm-official

Accepted papers will be included in the ACM Digital Library. 

Special  issues associated with the conference are being organized.

************ Topics ************

Papers on practical as well as on theoretical topics and problems in various topics related to rumors, fake news, misinformation, and disinformation during and after pandemics, are invited, with special emphasis on novel techniques and tools for automated tackling and curtailment of fake content during and after pandemics. Topics include(but are not limited to):

• AI approaches for the detection of online influence and manipulation
• AI approaches to identify misinformation and disinformation campaigns
• AI approaches for spotting misinformation and disinformation spreaders.
• Social media mining for automated detection of misinformation propagation and disinformation circulation
• AI approaches for automated identification and verification of claims
• AI approaches for intention detection for misinformation and disinformation contents
• AI approaches for credibility assessment of Social media sources
• AI approaches for fake news curtailment, filtering and prevention.
• AI approaches for analysis/detection of distributed and multi-platform misinformation and disinformation disseminations
• AI approaches for predicting the Impact of misinformation and disinformation during pandemics
• New datasets and evaluation methodologies to aid in automated detection and analysis of misinformation and disinformation content in social media channels

**********The Conference Sponsored by**********

Association for Computing Machinery's Special Interest Group on Computers & Society http://www.sigcas.org/

This workshop is supported by the Association of Cyber Forensics and Threat Investigators (www.acfti.org) and the Industrial Cybersecurity Center (www.cci-es.org).

########################################################################

This message was issued to members of www.jiscmail.ac.uk/SOCIOTECH, a mailing list hosted by www.jiscmail.ac.uk

Thanks to Andrew Zayine.

AI: Watch your P's and Q's

individual

|

INTERPERSONAL : SCIENCES

humanistic ----------------------------------------------- mechanistic

SOCIOLOGY : POLITICAL

|

group

"How to Talk When a Machine Is Listening:	PROCESS
PRACTICE	Corporate Disclosure in the Age of AI" ...

... and still ensure that corporate responsibilities are achieved (surpassed), value and values - ethical and social are upheld.

Cao, Sean S. and Jiang, Wei and Yang, Baozhong and Zhang, Alan L., How to Talk When a Machine is Listening: Corporate Disclosure in the Age of AI (August 31, 2020). Available at SSRN: https://ssrn.com/abstract=3683802 or http://dx.doi.org/10.2139/ssrn.3683802

My source:

Wigglesworth, R. (2020) Robo-surveillance shifts tone of CEO earnings calls, FT Weekend, 5-6 December, p.19. 

 

The 4P's in Hodges' model:

SCIENCES: Process

INTRA- INTERPERSONAL: Purpose

SOCIOLOGY: Practice

POLITICAL: Policy

ERCIM News No. 123 Special Theme: "Blue Growth"

Dear ERCIM News Reader,

ERCIM News No. 123 has just been published at https://ercim-news.ercim.eu/

This special theme is devoted to the application of ICT technologies to the "blue growth" field, which includes machine learning and artificial intelligence, cyber-physical systems of systems, IoT/M2M communications, space communications and observations, big data infrastructures, unmanned and autonomous systems.

Guest editors: Alberto Gotta (ISTI-CNR) and John Mardikis (EPLO - Circular Clima Institute)

This issue is also available for download in pdf and ePub.

Thank you for your interest in ERCIM News. Feel free to forward this message to anyone who might be interested.

Next issue:
No. 124,  January 2021
Special Theme: "Epidemic Modelling"

Announcements in this issue:

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Call for Proposals: Dagstuhl Seminars and Perspectives Workshops
Schloss Dagstuhl – Leibniz-Zentrum für Informatik is accepting proposals for scientific seminars/workshops in all areas of computer science, in particular also in connection with other fields. https://www.dagstuhl.de/dsproposal

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Seven open positions from PhD students to research scientists at the the SIMULA HPC department
https://www.simula.no/about/job-openings/simula-research-laboratory

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Positions available at Inria
Throughout the year, Inria welcomes new employees to its research teams and departments, whether through competitions, mobility within the public service, contractual agreements or internship proposals
https://jobs.inria.fr/public/classic/en/offres

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Special Issue on “Test Automation: Trends, Benefits, and Costs”
Call for papers and submission information:
https://www.journals.elsevier.com/journal-of-systems-and-software/call-for-papers/special-issue-on-test-automation-trends-benefits-and-costs

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ERCIM News
is published quarterly by ERCIM, the European Research Consortium for Informatics and Mathematics.
The printed edition reaches about 10000 readers.
This email alert reaches more than 8000 subscribers.
Advertise in ERCIM News

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About ERCIM
ERCIM - the European Research Consortium for Informatics and Mathematics - aims to foster collaborative work within the European research community and to increase co-operation with European industry. Leading European research institutes are members of ERCIM. ERCIM is the European host of W3C.

https://www.ercim.eu/
@ercim_news
ERCIM LinkedIn Group
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-- 
Peter Kunz                      	
ERCIM Office

2004, Route des Lucioles
BP93
F-06902 Sophia Antipolis Cedex

https://www.ercim.eu
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Ack. Thanks to Peter Kunz.

ERCIM News No. 122 Special theme "Solving Engineering Problems with Machine Learning"

Dear ERCIM News Reader,

ERCIM News No. 122 has just been published at https://ercim-news.ercim.eu/


This special theme explores different fields in which ML algorithms can help engineers to create designs with increased performance and reduced consumption, identify hidden dependencies and anomalies, and optimise and control manufacturing.

Guest editors: Noémi Friedman (Institute for Computer Science and Control (SZTAKI)) and Abdel Labbi (IBM Research – Europe)

The special the includes a keynote by Christopher Ganz, Head of Solutions & Standards of ABB Future Labs: "Machine Learning in Engineering - A view from industry"


The section "Research and Society" features a selection of articles on "Machine Ethics" coordinated by Erwin Schoitsch.

This issue is also available for download in pdf and ePub.

Thank you for your interest in ERCIM News. Feel free to forward this message to anyone who might be interested.

Next issue:
No. 123,  October 2020
Special Theme: "Blue Growth"

Announcements in this issue:

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Call for Proposals: Dagstuh Seminars and Perspectives Workshops
Schloss Dagstuhl – Leibniz-Zentrum für Informatik is accepting proposals for scientific seminars/workshops in all areas of computer science, in particular also in connection with other fields. https://www.dagstuhl.de/dsproposal

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ERCIM "Alain Bensoussan" Fellowship Programme - postdoctoral fellowships available at leading European research institutions.
Simple application procedure. Next application deadline: 30 September 2020
https://fellowship.ercim.eu/

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HORIZON 2020 Project Management
https://www.ercim.eu/activity/projects

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ERCIM News
is published quarterly by ERCIM, the European Research Consortium for Informatics and Mathematics.

---

About ERCIM
ERCIM - the European Research Consortium for Informatics and Mathematics - aims to foster collaborative work within the European research community and to increase co-operation with European industry. Leading European research institutes are members of ERCIM.
ERCIM is the European host of W3C.

Follow us on twitter @ercim_news
https://twitter.com/ercim_news
and join the open ERCIM LinkedIn Group http://www.linkedin.com/groups/ERCIM-81390

-- 
Peter Kunz                       
ERCIM Office
2004, Route des Lucioles
BP93
F-06902 Sophia Antipolis Cedex

See also on W2tQ:
'Engineering'

ERCIM News No. 116 Special theme "Transparency in Algorithmic Decision Making"

Dear ERCIM News Reader,

ERCIM News No. 116 has just been published at https://ercim-news.ercim.eu/

This issue includes:

- a Keynote by Sabine Theresia Köszegi, presenting the EU High-Level Expert Group on Artificial Intelligence.

- a Special Theme "Transparency in Algorithmic Decision Making", coordinated by the guest editors Andreas Rauber (TU Wien and SBA), Roberto Trasarti and Fosca Giannotti (ISTI-CNR), providing an overview of the range of activities in this domain.

- the section Research and Society about Ethics in Research, jointly coordinated by ERCIM (Claude Kirchner, Inria) and Informatics Europe (James Larrus, EPFL)

- the section "Research and Innovation" with news about research activities and innovative developments from European research institutes.

This issue is also available for download in pdf and ePub.

Thank you for your interest in ERCIM News. Feel free to forward this message to anyone who might be interested.

Next issue:
No. 117,  April 2019
Special Theme: "5G"

Peter Kunz                       
ERCIM Office
2004, Route des Lucioles
BP93
F-06902 Sophia Antipolis Cedex

Is Hodges' model a Self-Organising Hypothesis Network?

"The proposed approach is based on 3 key steps. First, derive knowledge from different sources of information (experimental data, expert learning, machine learning). Secondly, unify the different knowledge representations. Finally, organise the unified knowledge in a way that captures its generalisation hierarchy and facilitates the design of efficient prediction algorithms (Figure 3)." page 2 of 21.

Figure 3 The SOHN methodology. Different sources of knowledge are unified using a common representation based on the concept of hypothesis. The hypotheses can be organised into a hierarchical network to capture the knowledge in a standardised way (page 3 of 21).

Straight away this figure in Hanser et al. (2014) suggested learning and learners and the four care domains of Hodges' model. There are profound differences of course.

The information at the start takes the form of concepts, data, but 'information' also applies. The context in combining chemistry and informatics is radically different when it comes to who, or what is learning in that first arrow. The paper's keywords are:

Machine learning Knowledge discovery Data mining SAR QSAR SOHN Interpretable model Confidence metric and Hypothesis Network.

To a healthcare or social care student the knowledge encountered may well be raw. The principle of Hodges' model encourages the generation of hypotheses within and then across the model's knowledge domains. The learn-er can then attempt to unify these thoughts and reflections, organising them in a variety of ways. Hodges' model is not itself in self-organising, but there is a pattern-learning process for the learner and a pattern-matching process for the expert or specialist.

Hanser, T., Barber, C., Rosser, E., Vessey, J., Webb, D., & Werner, S. (2014). Self organising hypothesis networks: A new approach for representing and structuring SAR knowledge. Journal of Cheminformatics, 6(1), 1-21.

ERCIM News No. 107 Special theme: "Machine Learning"

Dear ERCIM News Reader,

ERCIM News No. 107 has just been published at http://ercim-news.ercim.eu/en107

This issue features :

- A Special Theme presenting a selection of articles about current trends and new paradigms in Machine Learning, coordinated by the guest editors Sander Bohte (CWI ) and Hung Son Nguyen (University of Warsaw).

- A Research and Society section dedicated to Open Access - Open Science, coordinated by Laurent Romary (Inria).

- A "Research and Innovation" section with news about research activities and innovative developments from European research institutions

This issue is also available for download in pdf and ePUB

Thank you for your interest in ERCIM News. Feel free to forward this message to others who might be interested.

Next issue: No. 108, January 2017 - Special Theme: "Computational Imaging"

Best regards,
Peter Kunz
ERCIM News editor in chief