Making sure that AI applications are trustworthy and ethically aligned is becoming a major issue for all developers of AI, and for all companies using AI. The European Artificial Intelligence Act (AI Act) has been endorsed by the European Parliament in December 2023, and will be put into place in the very near future – this will fuel the need for actually guaranteeing that AI is consistent with legal requirements on trustworthiness.
But: the way from legal requirements to testable properties of a concrete implementation is long. How to keep track of the relevant legal requirements? How to operationalize them into technical requirements? How to guarantee that a specific application is consistent with all requirements, over the whole lifecycle of the application?
This lunch event will explore these questions with an input presentation and a following discussion/exchange.
Elena Maran, Global Head Financial Services & RAI, Modulos AG, Zurich
Elena Maran is a former financial services executive with more than 13 years experience in the industry in different roles spanning from sales and trading to corporate banking. She is now Global Head Financial Services and Responsible AI at Modulos AG, defining the strategy, capturing requirements and driving growth in the sector. She is helping financial institutions embracing responsible AI governance and align with global and sector relevant AI regulations.
Join the discussion on a hot topic in Responsible AI and register here. The link to the webinar will be sent to you with the booking confirmation.
Combining techniques of technology foresight, storytelling, and sharing of lived experiences, Apéro Digital facilitates the co-creation of reflexive environments to support the understanding of societal transformations around digitalisation. Each event will result in a tangible artefact that is co-produced by participants. These outputs may be technical, argumentative, artistic, or analytical, all with the aim of adding values to the collective reflections about, and strategic navigation around, societal challenges posed by the ongoing digital transformation.
The 2024 Smart Services Summit invites academics, industry experts, and practitioners to explore the transformative impact of digital technologies and artificial intelligence on value co-creation within service ecosystems. This year’s theme emphasizes the critical intersections between technology and collaborative value-creation processes, highlighting how these elements reshape business models, customer experiences, and service management.
Topics of Interest:
Digital Facilitation of Value Co-creation: How digital tools and platforms enhance value co-creation between providers and consumers.
AI-driven Innovations in Service Design: Exploring AI’s role in developing new service offerings and enhancing interaction between actors
Automating Customer Engagement: The impact of automation and AI on customer engagement strategies and outcomes.
Data Analytics in Value Perception: Using analytics to understand and enhance how different beneficiaries perceive and measure value.
Data Analytics for Sustainable Value Co-creation: Reconciling business and societal value co-creation with data and analyses.
Balancing value creation between individuals and organizations: Value for business organizations as an enabler or counterpart to value for individuals inside or outside (e.g. customers)
Integrating AI with Service-Dominant Logic: Application of service-dominant logic in AI-driven service environments to foster collaborative value creation.
Ethical Considerations in AI-enabled Services: This section addresses the ethical implications of using AI in service delivery, particularly regarding privacy, transparency, and equity.
Case Studies on AI and Value Co-creation: Real-world examples of successful AI applications that have led to innovative co-creation practices.
Value from regulations: New EU regulations on data ownership in B2B and B2C markets offer the opportunity to improve data governance and lead to value co-creation.
Contributions are expected to be rigorously researched and provide new insights into the challenges and opportunities presented by digital technologies and AI in the context of value co-creation. All submissions will undergo a peer review process, with accepted papers to be included in the conference proceedings published by Springer.
As with previous years, we are looking for early-stage research and will publish the proceedings with Springer again. Furthermore, we will use industry to set the scene and the context from their position and follow them with impactful academic presentations.
Smart Services Industry 4.0 Product-Service Systems Value Co-creation Service Quality Service Science Service Design
Submission procedure
i. Write a short abstract: https://easychair.org/conferences/?conf=3s2024 ii. Short abstract submission: 1 July 2024 iii. Notification of acceptance: 14 July 2024 iv. Full paper submission: 14 September 2024 Acceptance of papers is based on the full paper (up to 12 pages in length, including references). All papers will be peer-reviewed and published by Springer.
Templates
There is no template for the abstract. Word template for the papers: https://bit.ly/4aV5hRd For initial submission, please submit only a PDF without author details. For final submission, please submit both PDF and DOC versions. Our conference will use APA style for references and papers will be limited to 12 pages.
Proceedings from 2023
The proceedings from 2023 will be published in June 2024.
In unserer zunehmend vernetzten Welt steigen die Cyber-Bedrohungen. Mit fortschrittlichen Technologien wachsen nicht nur die Geschäftsmöglichkeiten, sondern auch die Risiken wie Datendiebstahl und Cyberangriffe. Besuchen Sie unser Event, tauschen Sie sich aus, lernen Sie von führenden Experten und entwickeln Sie mit uns Strategien für eine sicherere digitale Zukunft. Neben spannenden Vorträgen zu Themen wie Herausforderungen an Hochschulen, digitaler Resilienz und der Evolution der Passwortsicherheit, bieten wir auch einen interaktiven Workshop an. Hier können Sie praxisnahe Lösungen erarbeiten und direkt anwenden. Freuen Sie sich auf tiefe Einblicke und praktische Erkenntnisse in der Cyber Security für die moderne Industrie 4.0. Wir freuen uns auf Ihre Teilnahme und Ihren Beitrag zu einem sichereren digitalen Morgen!
Weitere Informationen und die Registrierung finden Sie auf der offiziellen Homepage.
With the increasing availability of spatial data, analysis methods are also evolving. It is therefore not surprising that, in addition to established approaches from the field of machine learning, Large Language Models, which are very present in the media, are also used when working with spatial data. But are these sometimes very complex methods only to be found in research or are there already concrete applications and operational services in Switzerland? Examples from research and practice are presented, which are convincing with new methods of spatial data analysis.
Chris Bochsler from Cando uses a practical example in the field of energy management to show how AI enables new, smart services. Both customer documents and real-time data are linked to an LLM (RAG) in order to achieve even more relevant results. This with full consideration of data protection and privacy.
Key Speaker
Christoph B. Bochsler Managing Partner Cando
Online, Participants get an access link after registration. 25. April 2024, 11.45h – 12.15h
The next Expert Meeting of the NLP group on 9 April 2024, 17:30-19:00, will focus on “LLMs in Practice” and includes the following speakers:
Flurin Gishamer, Senior Data Scientist at Open Systems Title: “Harnessing Large Language Models for Augmenting Managed Service Operations”
Marcel Neidinger, Solution Architect at Amazon Web Services (AWS) Title: “Patterns and Lessons Learned from Building GenAI Applications in the Wild”
Arben Sabani, Language Technology Software Developer at SuperText Topic: “Leveraging LLMs for Complex Task Solving in Agent Systems”
It will take place at the ZHAW premises in Lagerstrasse 45, 8004 Zurich in room ZL O3.08 (3rd floor). The meeting will be followed by an apéro.
Online participation is also possible.
Please use the following form to confirm your attendance by March 31: https://forms.gle/iPk6PfFiWa58xz1j7. We will then send you a calendar invitation which also includes online participation details. (Note that the registration form also contains information on the SwissNLP General Assembly, which takes place right before the Expert Meeting, but this is only relevant to members of SwissNLP.)
Die generative KI (GenAI) zur Umsetzung natürlich-sprachlicher Fragen in SPARQL- und SQL-Abfragen zeigt bereits erstaunliche Ergebnisse. In der Lehre bietet sie den Studierenden einen niederschwelligen Zugang zu diesen deklarativen Datenbankabfragesprachen. Am Beispiel von QLever und anderen Werkzeugen werden der Stand der Forschung und der Einsatz in der Lehre vorgestellt. Auch Anwendungen wie die Konvertierung und Abfrage von Daten aus OpenStreetMap (OSM) werden behandelt. Dabei werden auch Probleme aufgezeigt. Beispielsweise hat GenAI die Schwäche, dass falsche Entity Identifier generiert werden, was zu unbrauchbaren Abfragen führt. Ein anderes Problem ist das Matching von Entitäten zwischen OSM und anderen Datenquellen. Seien Sie bei diesem Databooster Webinar dabei, wir erwarten eine interessante Diskussion mit einer namhaften Referentin.
Dieses Webinar wird auf Deutsch gehalten.
Prof. Dr. Hannah Bast (Albert-Ludwigs-Universität Freiburg) ist im Bereich der angewandten Algorithmik aktiv und ihre Forschungsinteressen umfassen unter anderem Algorithmen für die Routenplanung, Aspekte des Information Retrieval (Indexerstellung, Abfrageverarbeitung, Benutzerschnittstellen, ganze Informationssysteme) und die Verarbeitung natürlicher Sprache, mit und ohne Deep Learning
The Innovation Booster Databooster is organizing the Project Day, where previously supported innovation teams will present their projects and their developments to companies and interested partners.
Selected expert groups from the data innovation alliance will present themselves at this half-day event. Current projects, trends and potential collaborations will be presented, discussed and worked on in interactive sessions.
Welcome speech by FHNW: Eyes on Human-Data Interaction by Prof. Dr. Arzu Çöltekin, FHNW
14:15
Keynote Lessons learned on scaling after 1 year of GenAI by Dr. Marcin Pietrzyk, co-founder and CEO of Unit8
14:45
Expert Group Break-out (1)
15:30
Coffee Break
16:00
Expert Group Break-out (2)
17:00
Apéro
17:45
Closing
Prof. Dr. Arzu Çöltekin, FHNW
Arzu Çöltekin is a professor of Human-Computer Interaction, Visualization and Extended Reality, and leads the Institute of Interactive Technologies at the University of Applied Sciences and Arts Northwestern Switzerland. She is also a research affiliate at the Seamless Astronomy group in the Harvard-Smithsonian Center for Astrophysics of the Harvard University in Cambridge, USA, collaborating on scientific data analysis and visualization research. She chairs the international Extended Reality and Visual Analytics working group with the ISPRS; co-chairs the Commission on Geovisualization with the ICA, and is a council member with the International Society of Digital Earth (ISDE). Her interdisciplinary work covers topics related to information science, visual analytics, visualization and cartography, virtual/augmented reality, gaze-contingent displays, eye-tracking, vision (perception and cognition), and human-computer interaction.
Part 1: Predictive Maintenance @ABB: a Technology Company’s Point of View
Kai Hencken is Corporate Research Fellow for “Physical and Statistical Modeling” at the ABB Corporate Research Center, Baden-Dättwil, Switzerland. He holds a Ph.D. and a habilitation in theoretical physics from the university of Basel, where he is currently a lecturer. He joined the ABB Corporate Research Center in Baden-Dättwil in 2005 as a member of the theoretical physics group. His research interests are the combination of physical modeling, data analytics, and statistical methods to solve problems related to industrial devices. He works predominantly on developing diagnostics and prognostics approaches for different products, covering the range from sensors and signal processing to mathematical methods in prognostics.
Predictive Maintenance is one of the main application areas of the Industrial Internet of Things. The wide deployment of sensors and their connectivity allows to collect big amounts of data from devices in the field. The exponential increase of computing power and the recent developments in data analytics and machine learning makes the application of advanced algorithms possible. We are also facing changes in the way maintenance work is done and how its importance is seen.
ABB is a technology company providing devices and solutions in the area of electrification and automation. Many of their offerings in the area of digitalization and specifically predictive maintenance are geared towards their own products. This leads to topics that are specific for these cases in addition to the common ones.
In my talk I will discuss some of these issues and how they can be addressed: The domain knowledge and the simulation capabilities within the company are one of the big assets of any manufacturer. Reusing this for predictive maintenance solutions is an important aspect. For highly reliable products failure data will remain scarce even for a large installed base. This is a major bottleneck for any data-driven approach and needs to be overcome. The focus of many solutions developed is to provide monitoring and diagnostics capabilities. The prognostics aspect and the proposal of actions to be taken to remedy potential problems are often more important for the final customer. Examples are taken predominantly from electrification and motion devices.
Part 2: Discussion of combining physics and domain knowledge with AI for intelligent maintenance and operation
14:45 – 14:55 – Intro and introductions
14:55 – 15:30 – Presentation: Nicole Königstein, Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG: “Financial Times Series Prediction in the Age of Transformers”+ Open discussion and Q&A
15:30 – 16:00 – Break
16:00 – 16:30 – Presentation: Guillaume Raille, Engagement Director & Data Scientist at Unit8 SA: “LLMs beyond Chatbots: Unveiling the challenges of advanced LLM applications based on a real-world use cases“+ Open discussion and Q&A
16:30 – 17:00 – Discussion on topics that might be relevant for the DIA in the future and how to organize
In the field of environmental monitoring, artificial intelligence (AI) coupled with probability maps emerges as a powerful tool for comprehensively understanding and managing ecological systems. By harnessing machine learning algorithms, intricate patterns within environmental datasets can be discerned with unprecedented accuracy. Based on this understanding, probability maps can be calculated to offer valuable insights into the likelihood of various environmental events. These maps serve as crucial decision-making aids for policymakers, conservationists, and researchers alike, enabling proactive measures to mitigate ecological threats and promote sustainable practices.
Schedule:
14:45 – 14:55 – Intro and introductions (Dr. László István Etesi, Prof. Gerd Simons – FHNW)
14:55 – 15:30 – Probability Maps: Current research & applications in the field of environmental monitoring
15:30 – 16:00 – Break
16:00 – 16:30 – Indicate challenges around robust multi-sensor & multi-scale data integration and harmonization
16:30 – 17:00 – Discussion on ideas which can be further evaluated in the frame of the Innovation Booster
14:45 – 15:30 1. Growing with Data and AI, dealing with Governance. Introduction to the objectives of the new Expert Group in planning (Philipp Kuntschik, adesso Schweiz AG & Dr. Sarah Seyr, HSLU) 2. Transparency and Privacy for Data Governance – Can we have both? (Dr. Omran Ayob, SUPSI) 3. AI Maturity Framework (Frank Seifert, adesso Schweiz AG)
15:30 – 16:00 – Break
16:00 – 17:00 Maintaining integrity along the Data and AI value chain (interactive session): – Explore data governance practices from data collection to data protection. – Discuss algorithmic health and management of AI systems. – Engage in user-centered communication and transparency strategies.
Manage Cookie Consent
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
Functional
Always active
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Statistics
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Marketing
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.
