In a world increasingly driven by algorithms and automated systems, the need for trust, transparency, and human-centered design in artificial intelligence (AI) is greater than ever. While many visionaries aim to scale AI systems to industrial levels, few focus on making these systems explainable, verifiable, and ethical. Constance Wendrich, Director of External Affairs at the Berlin-based company MOTOR Ai, is one of the most impressive voices shaping one of the most disruptive technologies of our time: autonomous driving.
Her work combines cutting-edge engineering, regulatory vision, and a deep commitment to ethical innovation. In this article, we analyze Wendrich’s contributions to explainable AI (XAI), examine MOTOR Ai’s technological architecture, and demonstrate how she is actively shaping both policy and public debate on trustworthy AI.
From the Foreign Office to algorithm control: The path of a tech diplomat
Born in Germany, Constance Wendrich studied International Relations at Otto von Guericke University Magdeburg and Brunel University London. Her interdisciplinary background enabled her to analyze global systems—a skill she seamlessly transferred to the world of tech diplomacy.
Before moving into the field of autonomous vehicles, Wendrich worked in the German Bundestag and at media consulta. Her experience in political communications, public affairs, and negotiation laid the foundation for her current role as an interface between technology, the public, and regulation.
The technological heart of MOTOR Ai
At MOTOR Ai, Wendrich works with a team of engineers and cognitive scientists to implement a clear vision: Autonomous mobility must not only work, but also be understandable and comprehensible.
Unlike other companies that rely on opaque deep learning models, MOTOR Ai is based on explainable logic, cognitive simulation, and limited machine learning.
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1. Next-generation sensor fusion
Typical autonomous vehicles use cameras, radar, and LIDAR. MOTOR Ai supplements these with microphones—and for good reason: The system uses acoustic signals to detect sirens, human voices, or mechanical defects, for example.
Sensor fusion is achieved using Bayesian inference models and Kalman filters. The key combination is:
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Rule-based decision trees : For standardized traffic situations.
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Cognitive architectures (based on SOAR and ACT-R) : To simulate human decision making.
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Limited Deep Learning : Only for specialized pattern recognition, under human supervision.
This hybrid model forms the basis for a system that not only reacts but can justify its decisions.
2. Cognitively inspired decision models
MOTOR Ai combines symbolic logic with vector embeddings from neural networks – an approach from neuro-symbolic AI. This enables the vehicle to not only act but also explain why it acts.
Example:
“A pedestrian was detected at a distance of 4.2 m, crossing the traffic light. Based on historical risk profiles and the current speed, a gentle evasive maneuver was chosen, reducing the vehicle’s speed to 12 km/h to avoid a rear-end collision.”
These justifications are generated using a proprietary language module based on GPT-like language models and specialized for accident reports.
3. Auditable Decision Trees (ADT)
MOTOR Ai has developed a framework where every decision is logged in a verifiable data structure. Each node stores:
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Sensor status
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Reasons for the decision
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Actuator commands
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Trust values
These protocols are immutable, cryptographically secured and can be evaluated by authorities or insurance companies – a milestone in the regulation of autonomous systems.
Wendrich’s role: Trust through technology communication
Constance Wendrich significantly shapes MOTOR Ai’s corporate culture. As the interface between politics, the public, and industry, she ensures that explainable AI is not only developed, but also understood and accepted.
Their activities include:
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Lobbying EU bodies : For an XAI requirement in the AI Regulation.
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Cooperation with insurers : To develop new liability models based on explainable systems.
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Citizen dialogues : In the “Explain the journey to me” initiative, citizens were able to ask questions about the vehicle logic during a demo drive – live and transparently.
Programming technology with ethics
Explainability isn’t just a UI feature; it starts in the code. MOTOR Ai’s software architecture is based on:
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Rust for safety-critical components
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Python for machine learning
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Interpretability hooks in TensorFlow & PyTorch to store attention maps and gradients
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Formal verification to validate logical invariants in the driving decision tree
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CI/CD simulations with ethical dilemmas : e.g., “Child on the road vs. avoiding a rear-end collision”
Each case is compared with ISO 26262 standards. The ethical dimension is an integral part of software development – largely initiated by Wendrich’s understanding of values.
Women in autonomous technology: Wendrich’s support
At the Digital Mobility Summit 2025, Wendrich initiated a mentoring program for young women in STEM professions. She collaborated with Isabell Gradert (Airbus) and Ute Bonde (VBB) to publish the study “Intersectional Future: Ethical AI Systems through Diversity.”
The result: 40% more female technical hires at MOTOR Ai since 2023. Their work shows that diversity creates better, fairer technology.
The future: AI with a moral compass
For Wendrich, the biggest challenge in autonomous driving is not technical but philosophical:
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How do you code judgment?
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How do you define “reasonable” behavior in complex situations?
Your suggested solutions:
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Behavioral economics as a modeling basis for risk assessment
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Cultural contextualization : Vehicles should “think” differently regionally
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Ethics API : Users could set preferences within legal frameworks (e.g. driving styles or risk tolerance)
This proposal is currently being tested in pilot projects.
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Conclusion: Wendrich’s legacy
Constance Wendrich is more than just a communicator—she is the architect of a new model of trust between humans and machines. At a time when AI is shaping our world, she ensures that we don’t blindly accept these systems, but rather understand and question them.
Autonomous vehicles may never have a “conscience” – but thanks to visionaries like Constance Wendrich, they can at least act responsibly.
