Recommended Free Tools
iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Amsterdam’s documented benefits experiment tested a part-time-work premium and different forms of guidance—not an identified AI system. Its findings come from comparisons between participants and similar non-participants, so they should not be read as proof that AI changed welfare outcomes. For humanoid robots, safety also means assessing mental wellbeing, privacy, cybersecurity, human oversight, and whether testing reflects the people and settings involved—not just whether a machine avoids collisions.
What Amsterdam’s welfare experiment actually tested
The Amsterdam Experiment with Social Assistance began on 1 February 2018. It examined whether an incentive could encourage people receiving benefits to take part-time work. Participants who worked part-time could receive a premium of up to €200 per month. The city also examined different forms of guidance.
The city’s stated question was whether providing the premium affected participation in part-time work and exits from benefits into paid work, including whether employment lasted. The published evaluation matched participants with benefit recipients who had similar characteristics but did not participate. This was a matched-comparison design, not a randomized trial, and the city publication does not identify the experiment as an AI deployment.
Reported outcomes for participants who had not previously worked part-time
Gemeente Amsterdam, Onderzoek en Statistiek reported the following results in 2021. Percentages compare the experiment group with its matched comparison group within each intake.
#1 Best Overall
- BUILD, CODE & DRIVE YOUR OWN ROBOT CAR: Turn coding, electronics and engineering into a working programmable robot car you can assemble, program and drive; ideal for weekend family projects, STEM classrooms, coding clubs, robotics lessons and maker challenges
- EXPLORE FPV, LINE TRACKING & OBSTACLE AVOIDANCE: Control the robot with the ELEGOO app or IR remote, view live FPV video through the onboard camera, follow black lines, avoid obstacles with the ultrasonic sensor and explore multiple interactive driving modes
- BEGINNER-FRIENDLY BUILD WITH GUIDED WIRING: Keyed XH2.54 connectors help reduce wiring mistakes, while the illustrated tutorial and example programs guide beginners step by step from chassis assembly and module connection to programming and the first successful run
- GO BEYOND ASSEMBLY WITH CREATIVE CODING: Program with Arduino IDE to explore movement, sensors and control logic, then modify example code to create custom routes, reactions and robotics experiments that develop coding, problem-solving and engineering skills
- COMPLETE RECHARGEABLE STEM ROBOTICS KIT: Includes an ELEGOO UNO R3 controller board, ESP32-WROVER-based camera and Wi-Fi module, line-tracking and ultrasonic sensors, motors, IR remote and a 2000 mAh rechargeable lithium-ion battery; recommended for ages 8+ with adult guidance for first-time builders
| Outcome | 2018 intake | 2019 intake |
|---|---|---|
| Part-time work participation | 38% in experiment group; 9% in comparison group | 20% in experiment group; 8% in comparison group |
| Exit from benefits to work above the benefit level | 25% in experiment group; 19% in comparison group | 15% in experiment group; 9% in comparison group |
| Sustained employment | 71% in experiment group; 63% in comparison group | 67% in experiment group; 64% in comparison group |
The city defined sustained employment as working above the benefit threshold for at least six consecutive months. These are outcomes reported for the study’s matched groups; they do not establish that the premium alone caused the differences, and they say nothing about an AI system’s effects.
Where to find the longer account
The 2023 report Naar een werkzame bijstand: Bevindingen uit het Amsterdams Experiment met de Bijstand looks back over more than four years of research into different forms of guidance. Sandra Bos, Paul de Beer, Judith Elshout, Mathieu Portielje, and Kim van Berkel authored the 136-page report, commissioned by the Municipality of Amsterdam and partly funded by the European Social Fund. Its print ISBN is 9789463014571.
Rank #2
- 【Humanoid Robot with ESP32】 Powered by ESP32 and 17 intelligent servos, Tonybot smart humanoid robot delivers smooth, dynamic performance. Use the app to easily control it for walking, dancing, kicking, and more. Tonybot can stand up automatically, which is great for playing football and performing gymnastics.
- 【Multimodal Large AI Models】Powered by an AI model module that combines language, voice, and vision models, Tonybot Ultimate Kit unlocks advanced embodied AI functions such as natural conversation and scene understanding. (Ultimate Kit Only)
- 【AI Vision & Voice Interaction】Equipped with an ESP32-S3 vision module and voice interaction module, Tonybot AI robot enables offline face recognition, target tracking, visual line following, voice control, and more. Customize commands and train it to be your AI assistant.
- 【Expandable AI Development with Sensors】 Tonybot robot kit comes with an ultrasonic sensor, IMU sensor, buzzer, and supports modules like dot matrix display, fan, temp/humidity sensors, and WiFi for endless AI-driven development.
- 【3 Programming Options & Comprehensive Tutorials】Tonybot smart AI robot supports Arduino, Python, and Scratch programming, with open-source low-level code and step-by-step tutorials covering everything from beginner learning to advanced humanoid robot development.
What the Amsterdam findings do—and do not—say about AI
The available Amsterdam publications describe an earnings premium and guidance research; they do not establish that AI was used to assess benefit recipients or determine their eligibility. The label “welfare AI experiment” therefore does not accurately describe the documented study. Any claim about a separate Amsterdam welfare AI system would need to identify that system and its role.
There is relevant Dutch public-sector guidance for algorithmic systems, but it should not be confused with evidence about this experiment. The Dutch government says the Impact Assessment Mensenrechten en Algoritmes (IAMA), developed by Utrecht University, was updated on 16 February 2026 to help public organisations consider possible human-rights impacts before developing or using algorithms. The government says the update aligned it with Article 27 of the AI Act, which it describes as requiring a fundamental-rights impact assessment for high-risk AI systems. That context does not show that IAMA was applied to the Amsterdam benefits study.
Rank #3
- Al-Driven & Raspberry Pi Powered. TonyPi is a high-performance AI vision robot designed for AI education applications. It is powered by the Raspberry Pi 5, integrated with an OpenCV image processing library and robotic inverse kinematics algorithms. Offering open-source access, TonyPi provides a flexible development environment that supports advanced AI robotics development.
- AI Large Model ChatGPT Integration for Enhanced Human-Machine Interaction. TonyPi incorporates a multimodal model, with ChatGPT at the core of its interaction system. With AI vision and voice integration, TonyPi excels in perception, reasoning, and action, enabling advanced embodied AI applications and delivering a seamless, intuitive human-machine interaction experience!
- AI Voice Command & Recognition. Equipped with ChatGPT, TonyPi accurately understands voice commands, analyzes visual scenes in its field of view, and carries out appropriate actions—enabling smooth and responsive voice interaction.
- AI Vision Recognition and Tracking. TonyPi's 2DOF head is fitted with an HD camera that provides a wide field of view. It supports a range of AI vision capabilities, including color recognition, target tracking, ball kicking, line following, and MediaPipe-based motion control for interactive AI applications.
- High-Voltage Intelligent Bus Servos. Equipped with 16 high-voltage intelligent bus servos, TonyPi offers rapid response times and stable output, enabling precise multi-joint coordination and complex motion control. This ensures accurate humanoid postures and interactive movements to meet various demands.
Why humanoid-robot safety is broader than collision avoidance
A robot can pose risks through physical contact, but safety also depends on how people experience and rely on it, how it handles data, and what happens when it fails or is attacked. A European Commission report published on 19 February 2020 discusses challenges arising from autonomy, connectivity, data dependence, learning, and system complexity. It flags possible mental-health risks from working or living alongside humanoid AI systems and calls attention to the needs of older people in care settings, including secure care relationships, control over daily routines, and being informed about those routines.
The Commission report is a policy discussion of risks and potential regulatory gaps, not a current product certification checklist. Later work reinforces the need to test robots in context and account for differences among users.
Rank #4
- High-performance Hardware Configurations.AiNex is developed upon Robot Operating System(ROS) and featuring a Raspberry Pi 5/4B, 24 intelligent serial bus servos, an HD camera, movable mechanical hands. It is a professional AI humanoid robot capable of lively mimicking human actions.
- Advanced Inverse Kinematics Gait.AiNex integrates inverse kinematics algorithm for flexible pose control as well as gait planning for omnidirectional movement.AiNex is equipped with two hip joints to support the rotation of the legs on the Z-axis, making the robot more flexible in turning.
- Robot Control Across Platforms.AiNex provides multiple control methods, like WonderROS app (compatible with iOS and Android system), wireless handle, and PC software.
- Outstanding AI Vision Recognition and Tracking.Leveraging technologies, like machine vision and OpenCV, AiNex excels in precise object recognition, enabling it to accomplish target.
- We offer an extensive collection of tutorials covering up to 18 topics.We offer an extensive collection of tutorials in English and Chinese.These tutorials cover wide range of topics, including getting ready!
Evidence on workplace monitoring is about perceptions, not robot injury rates
A preregistered vignette experiment reported in Milena Nikolova’s July 2026 IZA Discussion Paper 18782 asked 2,172 Dutch adults to evaluate otherwise identical workplaces with human-supervisor, AI-only, or hybrid AI-human safety monitoring. Respondents rated job satisfaction, work meaningfulness, and social value lower in both AI conditions than under human supervision. They also viewed AI monitoring as less respectful of privacy and dignity, while judging its effectiveness as comparable to human supervision; perceived fair wages changed little.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
These were evaluations of hypothetical workplace arrangements. They do not measure actual injuries, demonstrate how humanoid robots perform, or establish what workers in a real deployment would experience.
Best Value
- Al-Driven & Raspberry Pi Powered. TonyPi is a high-performance AI vision robot designed for AI education applications. It is powered by the Raspberry Pi 5, integrated with an OpenCV image processing library and robotic inverse kinematics algorithms. Offering open-source access, TonyPi provides a flexible development environment that supports advanced AI robotics development.
- AI Large Model ChatGPT Integration for Enhanced User-Machine Interaction. TonyPi incorporates a multimodal model, with ChatGPT at the core of its interaction system. With AI vision and voice integration, TonyPi excels in perception, reasoning, and action, enabling advanced embodied AI applications and delivering a seamless, intuitive human-machine interaction experience!
- AI Voice Command & Recognition. Equipped with Large Language Models, TonyPi accurately understands voice commands, analyzes visual scenes in its field of view, and carries out appropriate actions—enabling smooth and responsive voice interaction.
- AI Vision Recognition and Tracking. TonyPi's 2DOF head is fitted with an HD camera that provides a wide field of view. It supports a range of AI vision capabilities, including color recognition, target tracking, ball kicking, line following, and MediaPipe-based motion control for interactive AI applications.
- Comprehensive Learning Resources. TonyPi offers abundant educational content, including resources on robotic motion control, OpenCV, deep learning, MediaPipe, AI large models, voice interaction, and sensor applications. We provide extensive learning materials and tutorials to guide you from foundational concepts to advanced practices, helping you develop your AI humanoid robot.
How to assess whether a humanoid robot is safer for a real use
There is no single safety measure established here that applies to every humanoid robot. A meaningful assessment starts with the specific machine, its intended use, its environment, and the people expected to interact with it.
1. Define the setting and users
Separate industrial collaboration, public services, home use, and care work: a hazard that matters in a factory may differ from one involving a person who depends on a robot for daily support. Identify who may use or encounter the robot, including people with disabilities and older adults, and what control they retain over the interaction.
2. Check the applicable rules and standards for that deployment
The European Commission’s 2026 rolling plan describes ongoing standardisation work in robotics and autonomous systems, including the role of the Machinery Regulation and its relationship to AI requirements. The applicable framework depends on the machine, intended use, deployment environment, and current harmonised standards. A standard or regulatory label should not be treated as a blanket guarantee for every context.
3. Validate foreseeable hazards under controlled conditions
A 2024 academic discussion of experimental standardisation describes the EU-funded EUROBENCH project’s separate facilities for humanoid and wearable robots, designed to support rigorous, repeatable benchmarks. Controlled validation can help reveal hazards and inform standards. For a specific deployment, testing should reflect foreseeable failure cases and the conditions in which the robot will actually operate.
4. Include human, data, and security risks
- Physical safety: consider contact and other hazards created by the robot’s movement and operation.
- Mental wellbeing and human oversight: assess how people may experience working or living with the robot, and whether meaningful human supervision is available where needed.
- Privacy and data quality: consider what information the robot collects and whether data used in its operation are accurate and relevant.
- Cybersecurity: consider how connectivity and cyber-threats could affect safe operation.
- User variation: assess whether design and testing account for age, sex, gender, and disability rather than assuming one typical user.
The Commission’s 2020 analysis, the 2024 discussion of user-centred testing, and the 2026 standardisation overview are complementary: together they point toward evaluating physical and contextual hazards, but they do not certify any particular robot or settle which standard applies to an unnamed device.
Quick Recap
What to verify before accepting a safety claim
- Which robot, task, location, and user group does the claim cover?
- What rules and standards apply to that machine and use case, and are they current?
- What testing was conducted, under what conditions, and which foreseeable failures were included?
- Were privacy, data quality, cybersecurity, human oversight, and mental wellbeing considered alongside physical hazards?
- Did design and testing account for relevant differences in age and disability?
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
