The Trustworthy Artificial Intelligence Implementation (TAII) Framework Canvas is available on Miroverse now!
Trustworthy Artificial Intelligence Implementation - Introduction to the TAII Framework published at Springer in Business Guides on the Go
Organisations and companies need practical tools and guidelines to kick-off the implementation of Trustworthy Artificial Intelligence (TAI) Systems. The scientific research based TAII Framework takes a holistic approach to identify the systemic relationships of ethics for the company ecosystem and considers corporate values, business models, and common good aspects like the 17 Sustainable Development Goals and the Universal Declaration of Human Rights. The TAII Framework Canvas creates guidance to initiate the implementation of AI ethics in organisations without requiring a deep background in philosophy and considers the social impacts outside of a software and data engineering setting. Orgnizations and Universities do trust the TAII Framework. Contact us for a first step towards an ethical system development.
Three different online | offline packages. Course content: What is AI ethics? Values and norms. Ethical frameworks. Common good & well-being. Utilitarianism. Accountability. Transparency. Human rights. Data privacy. Safety & robustness. Bias. Fairness & non-discrimination. Ethics-washing. Guidelines & principles. Book an AI Ethics Workshop to kick off AI ethics in your organization, including certificate and exercises.
The AI Ethics Kickoff workshop guides from theory into doing the first steps for companies or institutions.
Trustworthy AI Implementation (TAII) generates new opportunities to define the value creation and how to create, deliver and capture sustainable value for your business. This is relevant both for developers of AI systems and for any business that will be disrupted by AI technology.
The TAII Framework generates a meta perspective on the systemic dependencies of ethics for the company ecosystem.
Innovation and implementation of AI technologies and services within the organization's core business model to strengthen the market position for the future.
The Trustworthy Artificial Intelligence Implementation Framework generates a meta perspective of ethics within the AI system developer's ecosystem by designing social impact. More information
“Teaching and training ethics is already a difficult task. Adding AI to the ethics discussion further complicates decision making for managers, but this book provides clear examples and urgency for it to be done. For practitioners and researchers who seek to help with organizational development and implementation of AI and AI ethics, this book can be a valuable asset. The scholarly studies cited … provide a rich empirical landscape from which to build a foundation for other empirical studies on Tall system implementation.”
"Josef Baker-Brunnbauer's new book on the application of a practical framework for safe and trustworthy AI is a must-read for anyone working in the field of AI and machine learning. The author expertly guides readers through the complexities of building AI systems that are not only effective, but also safe and trustworthy. With clear and concise explanations, practical examples, and a wealth of insights, this book is an invaluable resource for anyone looking to stay ahead of the curve in the rapidly-evolving field of AI.”
SocialTechLab.eu has been founded by Josef Baker-Brunnbauer during his research work at the University of Graz, Austria in 2019. The findings showed the need for Trustworthy AI (TAI) for a societal understanding and acceptance. It also demonstrated the challenges for companies to tackle the implementation of TAI. SocialTechLab.eu consists of an interdisciplinary team that designs and drafts future social tech concepts & studies for companies in order to generate human-centered experience and sustainable social impact with AI products and services. The TAII Framework® for AI companies combines methodologies from interdisciplinary professions like computer science, innovation, psychology and sociology.
The assessment of the seven key requirements reflects and possibly adapts the design and development process of AI systems. Therefore, it generates a dispute with social implications and responsibilities to contribute and shape a good society.
Some machine learning techniques, although very successful from the accuracy point of view, are very opaque in terms of understanding how they make decisions. Non-trustworthy black-box AI systems refer to scenarios, where it is not possible to trace back to the reason for certain decisions.
Prepare and adapt the AI design and development process to simplify the implementation of governmental regulation (e.g. EU AI Act) and certification. Communicate the taken social responsibility and shape a role model within your industry.
2021
New Business, IT- & Digitalisierungs-Guide: KI-Ethik-Workshops
Artificial Intelligence EU Conference: AI Research Hub
AI4EU Cafe: How to overcome the barrier to kickoff TAII
PERFORM European Digital Retail Summit: TAII Framework
DigitalCity.Wien: Digitale Montagsrunde
Innovation Value Institute: Digital Retail Webinar
AI Guild: Trustworthy AI
ETAPAS: Disruptive Technologies
European Commission: AI Alliance
enliteAI: AI Landscape Austria
2022
Montreal AI Ethics Institute MAIEI: Applying the TAII Framework on Tesla Bot
Montreal AI Ethics Institute MAIEI: How the TAII Framework Could Influence the Amazon’s Astro Home Robot Development
SSRN: TAII Framework Applied to Metaverse and AI Development a Case for Cyber Ethics
Medium: SocialTechLab.eu is working on ethics standards for Metaverse
AI4Good Foundation: Building climate-and-community responsibility companies
Springer: Trustworthy Artificial Intelligence Implementation
enliteAI: AI Landscape Austria
2023
Data Intelligence Offensive, DIO: SocialTechLab.eu und TAII-Framework
The Ethical AI Database, EAIDB: Collection of vetted, ethical AI companies
New Business Magazine: Künstliche Intelligenz
Miro: Miroverse - TAII Framework Canvas
European Commission: TAII Framework Canvas
Robonomics - The Journal of the Automated Economy: Book Review: TAII Framework
OECD.AI: Catalogue of Tools & Metrics for Trustworthy AI
The Ethical AI Database, EAIDB: Responsible AI Startup Ecosystem Map
M/O/T University Klagenfurt: ULG Daten- und KI-Management
M/O/T University Klagenfurt: Regulierung & Ethik im Spannungsfeld KI
European Commission AI Alliance: Holistic Framework for Trustworthy AI Implementation
European Commission AI Alliance: First Steps of Trustworthy AI Implementation by Using the TAII Framework Canvas
Brutkasten: Austrian AI Landscape 2023
AI Landscape Austria: 2023 edition AI Landscape
2024
ETSI: Artificial Intelligence (AI) Conference
European Commission: EC Library Guide on trustworthy artificial intelligence
M/O/T University Klagenfurt: ULG Daten und Künstliche Intelligenz-Management
European Commission: Artificial Intelligence (AI) Pact
ETSI / CEN: Workshop on EU Digital Identity Framework Standards
The Ethical AI Database: The Responsible AI Ecosystem, 2024H1 Map
European Union Agency For Cybersecurity: 10th Trust Services and eID Forum
EBSCON 2024: Electronic and Software Based Systems Conference
NVIDIA: AI Summit
World Summit AI: The AI Brains are Coming, Amsterdam
SOSV Climate Tech Summit: The Emerging Startup Ecosystem
it-sa 365: Home of IT Security
RegHorizon ETH Zurich: AI Policy Summit 2024
AAIC Austria: Applied AI Conference 2024
Forum Europe: Bringing AI Factories to Life