Work and AI 2030: Challenges and Strategies for Tomorrow's Work

Preface
Contents
Contributors
Social and ethical aspects of AI in the world of work
The Ghost of German Angst: Are We Too Skeptical for AI Development?
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on German Innovation Instead of German Angst 2030
5 Summary and Practical Recommendations
References
Practical Guide AI = All Together and Interdisciplinary
1 Introduction
2 Status Quo: What Expertise is needed for the Introduction of an AI System?
3 Challenges and Solutions
4 Outlook on Collaboration and Interdisciplinarity in 2030
5 Summary and Practical Recommendations
5.1 Accept the Design Challenge
5.2 Interdisciplinary Co-Design
5.2.1 Requirements
5.2.2 Available Data
5.2.3 Quality Measures
5.2.4 Conversion Process
5.2.5 Experimental Spaces
References
Future Collaboration between Humans and AI
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on AI in Human-Machine Teams in 2030
5 Summary and Practical Recommendations
References
AI, Innovation and Start-ups
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on AI, Innovations and Start-ups in 2030
5 Summary and Practical Recommendations
References
AI Demands Corporate Digital Responsibility (CDR)
1 Introduction
2 Status Quo and Case Studies
3 Challenges and Solutions
4 Outlook on AI-Supported Workplaces in Companies with CDR in 2030
4.1 Voluntary Commitment to AI-Supported Workplaces that Goes Beyond AI and Data Regulation can Create Competitive Advantages
4.2 AI Ethics and Governance Alone are not Enough for Credibility in Dealing with Algorithms
4.3 CDR Develops an Organisational Framework that Enables Trust and Credibility Among All Stakeholders, Especially Among Employees
5 Summary and Practical Recommendations
References
AI Ethics and Neuroethics Promote Relational AI Discourse
1 Introduction: ‘Artificial Intelligence’ as a Result of Dualistic Knowledge Production
2 Status Quo
3 Challenges and Solutions
4 Outlook on AI Discourse in 2030
5 Summary and Practical Recommendations
References
Legal aspects of AI in the world of work
Digital Product Monitoring Obligations for Smart Products
1 Introduction
2 Status Quo/Inventory and Case Studies
2.1 Which Product Liability Law Applies to Manufacturers of Smart Products?
2.2 The Current Product and Producer Liability as Possible Civil Law Bases for a Digital Product Monitoring Obligation
2.3 The ProdSG as a Possible Regulatory Basis for a Digital Product Monitoring Obligation
3 Challenges and Solutions
3.1 Initial Situation: No Explicitly Regulated Digital Product Monitoring Obligation
3.2 Meaningfulness of a Digital Product Monitoring Obligation for Smart Products
3.2.1 Merging of Safety and Security
3.2.2 The Problem of So-Called Opacity of AI
4 Outlook on a Digital Product Monitoring Obligation in 2030
4.1 Forecast: The Digital Product Monitoring Obligation will Come
4.2 Effectiveness of a Digital Product Monitoring Obligation
4.3 Regulatory Management Systems (Example: Automotive Sector)
4.4 Technical Norms and Standards: Security of Connected (IoT-)Consumer Products
5 Summary and Practical Recommendations
References
The Use of AI-Based Speech Analysis in the Application Process
1 Introduction
2 Status Quo
3 Challenges and Solutions
3.1 Data Protection Law
3.1.1 Consent
3.1.2 § 26 I 1 BDSG Necessity
3.1.3 Permissible Degree of Automation of the Selection Process
3.2 Discrimination/AGG
4 Outlook on AI-Based Language Analysis in the Application Process in 2030
5 Summary and Practical Recommendations
References
Individual Labour Law Issues in the Use of AI
1 Introduction
2 Status Quo: Framework Conditions for the Use of AI in the Employment Relationship
3 Legal Challenges and Solutions
4 Intermediate Result and Evaluation
5 Outlook on AI in the Employment Relationship in 2030
6 Summary and Practical Recommendations
References
AI in the Company: Is the Employer or the AI as an e-Person Liable?
1 Introduction
2 Status Quo
2.1 AI and Associated Risks
2.2 The Current Liability Regime
3 Challenges of the Current Liability Regime and the e-Person as a Possible Solution Approach
3.1 The Liability of AI as an e-Person
3.2 The Criticism of the e-Person
3.3 The e-Person is Currently not a Solution
4 Outlook on Employer Liability for AI in 2030
5 Summary and Practical Recommendations
References
The Co-Determination Right of the Works Council According to § 87 Para. 1 No. 6 BetrVG in the Use of AI Systems in the Company
1 Introduction
2 Status Quo/Inventory and Case Studies
2.1 Interpretation in Case Law and Literature
2.2 Examples of Implementation
3 Challenges and Solutions
4 Preview of AI in the Context of Co-Determination Rights in 2030
5 Summary and Recommendations for Employers
References
Data Protection Assessment of Predictive Policing in the Employment Context
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on Predictive Policing in 2030
5 Summary and Practical Recommendations
References
Legal Requirements for AI Decisions in Administration and Justice
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on AI Systems in Administration and Justice in 2030
5 Summary and Practical Recommendations
References
AI in the economic world of work
Intelligent IT Systems in Business Application
1 Introduction
2 Status Quo
3 Challenges in Building Trust
4 Possible Solutions: Control and Transparency
5 Actionable Recommendations and Outlook
References
Successful Introduction of AI in the Company
1 Introduction
2 Status Quo—Assessments and Fears Regarding the Introduction of AI
3 Challenges and Solutions
4 Outlook on the Introduction of AI in Companies in 2030
5 Summary and Practical Recommendations
References
Responsible and Robust AI in Companies
1 Introduction
2 Status Quo and Case Studies
3 Challenges and Solutions
4 Outlook on Mastering AI-Related Risks in 2030
4.1 Strategic Anchoring
4.2 Data and Training
4.3 Processes and Governance
4.4 Technical Tests and Automation
5 Summary and Practical Recommendations
References
AI as a Driver of Hybrid Forms of Employment
1 Introduction
2 Status Quo/Case Studies
3 Challenges and Solutions
4 Outlook on AI as a Driver of Hybrid Forms of Employment in 2030
5 Summary and Practical Recommendations
References
Digital Finance—The Future of Financial Planning in Companies
1 Introduction
2 Status Quo
3 Challenges and Solution
4 Outlook on AI-based Financial Planning by 2030
5 Summary and Practical Recommendations
References
AI in Banks
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on AI in Banks in 2030
5 Summary and Practical Recommendations
References
AI in the industrial world of work
Potentials of AI for Production
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on AI in Production in 2030
4.1 The Scenario Map of AI-Based Work Environments 2030
4.2 A Design Dilemma
5 Summary and Practical Recommendations
References
The Grassroots Movement of AI
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on AI in the Energy Sector in 2030
5 Summary and Practical Recommendations
References
Employment Effects and Changes in Work Organisation Arising from AI
1 Introduction
2 Status Quo: Use and Effects of AI
3 Challenges and Solutions
4 Outlook on Employment Effects and Changes in Work Organisation Arising from AI by 2030
5 Summary and Practical Recommendations
References
Opportunities of AI for Work Design in the Manufacturing Industry
1 Introduction
2 Status Quo/Inventory and Case Studies
3 Challenges and Solutions
4 Outlook on AI in the Manufacturing Industry in 2030
5 Summary and Practical Recommendations
6 Funding Note
References
The Role of Humans in the Context of Sovereign Data Spaces
1 Introduction
2 Status Quo/Inventory: Data Markets in the Data Economy
3 Challenges and Solutions
3.1 Architecture of a Data Marketplace in an IoT Data Space
3.2 Approaches to Trading IoT Data and Services
4 Outlook on the Role of Humans in the Context of Sovereign Data Spaces in 2030
References
AI in the Crafts
1 Introduction
2 Status Quo: AI in Crafts 2021
3 Challenges and Solutions
4 Outlook on AI in the Industrial Working World in 2030
5 Summary and Practical Recommendations
References
AI in the mobile world of work and logistics
Potentials in the Field of Mobility by Mathematical Methods of AI
1 Introduction
2 Status Quo/Inventory and Case Studies
3 Challenges and Solutions
4 Outlook on AI Through Mathematical Methods in the Field of Mobility in 2030
5 Summary and Practical Recommendations
References
Mobility in Urban Areas
1 Introduction
2 Status Quo/Inventory and Case Studies
2.1 Traffic Control Systems
2.2 Repair and Maintenance
2.3 Autonomous Driving
2.4 Mobility as a Service
3 Challenges and Solutions
3.1 Handling Data Protection
3.2 Ethical Issues
4 Outlook on AI in Urban Mobility in 2030
5 Summary and Practical Recommendations
References
Industrial AI—Smart Factories and Team Robotics
1 Introduction
2 Status Quo/Inventory and Case Studies
3 Challenges and Solutions
4 Outlook on AI in Smart Factories and Team Robotics in 2030
5 Summary and Practical Recommendations
References
AI in the Automotive Industry
1 Introduction
2 Status Quo: An Industry in Transition
3 Challenges and Solutions
4 Outlook on AI in Automotive in 2030
5 Summary and Practical Recommendations
References
AI in the Rail Sector
1 Introduction
2 Status Quo
3 Challenges and Solutions
3.1 AI in Rail Operations: More Capacity and Higher Quality
3.2 AI for the Customer: Better Informed and Easier to Reach the Destination
4 Outlook on AI in the Mobile Work Environment in 2030
4.1 Changed Job Profiles & Composition of the Workforce
4.2 Growing Workforce and More Service for the Transport Transition
5 Summary and Recommendations
References
AI as an Opportunity for the Future Airline Business
1 Introduction
2 Current Status and Case Studies
2.1 Relief and Acceleration of Tedious Text Tasks by Natural Language Processing
2.2 Acceleration of Work Steps by Image Processing
2.3 Change of Work Processes by Forecasting Systems
3 Challenges and Solutions
3.1 AI as a Service
4 Outlook on AI as an Opportunity for the Future Airline Business in 2030
4.1 Check-In
4.2 Baggage Loading
4.3 Security Check
4.4 Boarding
4.5 Service on Board
4.6 Sustainability Enabled by AI
5 Summary and Practical Recommendations
References
AI in Intralogistics
1 Introduction
2 Status Quo: Use of AI in Intralogistics Today
3 Current Challenges for the Further Development of AI in Intralogistics
4 Outlook on AI in Intralogistics in 2030
5 Summary and Practical Recommendations
References
AI in the medical and pharmaceutical world of work
AI Makes Medicine More Efficient, Individual and Preventive
1 Introduction
2 Status Quo and Case Studies
2.1 Detecting Anomalies: AI and the Evaluation of Medical Image Data
2.2 Using Sensor Data: From Lifestyle Wearable to Health Monitoring
2.3 Information Systems: Data Mining for New Medical Standards
3 Challenges and Solutions: The Handling of Data must be Regulated
4 Outlook on AI in the Medical and Pharmaceutical Work Environment in 2030
5 Summary
References
AI in the Clinical Treatment Path
1 Introduction
2 Status Quo—Inventory and Case Studies
3 Challenges and Solutions
4 Outlook on AI in the Clinical Care Pathway in 2030
5 Summary and Practical Recommendations
References
To Make Medicine That No One Has Ever Seen Before
1 Introduction: From Isolated Solutions to Transformation
2 Status Quo/Stocktaking and Case Studies
3 Challenges and Solutions: Every Epoch Dreams of the Next
4 Outlook on AI in the Medical and Pharmaceutical Work Environment in 2030
References
AI in the Health Market
1 Introduction: Health Market in Transition
2 Inventory and Case Studies
2.1 Health Apps and Chatbots
2.2 Customer Advice and Customer Feedback
2.3 Care Pathway Analysis
2.4 Billing Audit
3 Challenges and Solutions
3.1 Transparency and Trust
3.2 Data Use and Data Protection
3.3 Digital Health Literacy
4 Outlook on AI in the Health Market in 2030
4.1 Prevention and the Health Insurance as a Health Partner
4.2 Empathy
4.3 Handling Data
5 Summary and Practical Recommendations
References
Data-Based Innovations in the Health Sector and Strategic Preparation of Well-Known Global IT Companies
1 Introduction
2 Status Quo
3 Challenges and Solutions: Strategies and Innovations for Market Entry into the Health Care Sector
4 Outlook on AI in the Medical and Pharmaceutical Work Environment in 2030
4.1 Data-Based Business Models as the Basis for New Fields of Work in Medicine
4.2 Patient-Generated Health Data and Electronic Health Records
5 Summary and Practical Recommendations
References
AI in education and training
Introductory Qualification on Artifical Intelligence
1 Introduction
2 Status Quo
3 Challenges and Solutions
4 Outlook on the AI Supplementary Qualification in 2030
5 Summary and Practical Recommendations
References
AI in Education: Educational Technology and AI
1 Introduction
2 Stocktaking and Case Studies: EdTech and AI
3 Challenges and Solutions
4 Outlook on AI in EdTech in 2030
5 Summary and Practical Recommendations
References
AI in Continuing Education of the Future
1 Introduction
2 Status Quo
2.1 Learning Analytics
2.2 Personalised Learning
2.3 Task Automation
2.4 Smart Content
3 Challenges and Solutions: Human Bias
4 AI in Further Education 2030
5 Summary and Practical Recommendations
References
AI in Vocational Rehabilitation—Intelligent Assistance for People with Disabilities
1 Introduction
2 Status Quo—AI in Vocational Rehabilitation
3 Challenges and Solutions
4 Results: Existing Technologies and Individual, Organisational and Technical Success Factors for Their Introduction, and Long-Term Use
5 Outlook on AI in Vocational Rehabilitation in 2030
6 Summary and Practical Recommendations
References