Computer-implemented method for generating at least one test data set for an algorithm that obtains image data as an input and outputs areas of action that are dependent upon the image data as an output, and/or said algorithm obtains sensor data as an input and outputs areas of action that are dependent upon the sensor data as an output, wherein the algorithm is used for controlling a vehicle or robot, and wherein the areas of action represent permissible control parameters, and wherein, when the control parameters are executed, the vehicle or the robot is triggered to move in the area of action, said method comprising the following steps: 1.1 a trained artificial intelligence is provided, said artificial intelligence comprising at least one generative adversarial network, 1.2 the artificial intelligence is stimulated using at least one random signal and/or using a quasi-linearity property for visual concepts and 1.3 the stimulated artificial intelligence generates at least one test data set that comprises image data and areas of action that are associated with the image data, and/or sensor data and areas of action that are associated with the sensor data, wherein in order to obtain the trained artificial intelligence that is provided in step 1.1, the following steps are implemented: 2.1 a learning data set is provided that comprises real image data that is recorded by means of at least one image capturing facility, and areas of action that are associated with the real image data, and/or real sensor data that is recorded by means of at least one sensor facility, and areas of action that are associated with the real sensor data, 2.2 an artificial intelligence is provided and 2.3 the artificial intelligence is conditioned using the learning data set that is provided. wherein the areas of action represent permissible control parameters, and wherein, when the control parameters are executed, the vehicle or the robot is triggered to move in the area of action, said method comprising the following steps: 1.1 a trained artificial intelligence is provided, said artificial intelligence comprising at least one generative adversarial network, 1.2 the artificial intelligence is stimulated using at least one random signal and/or using a quasi-linearity property for visual concepts and 1.3 the stimulated artificial intelligence generates at least one test data set that comprises image data and areas of action that are associated with the image data, and/or sensor data and areas of action that are associated with the sensor data, 1.1 a trained artificial intelligence is provided, said artificial intelligence comprising at least one generative adversarial network, 1.2 the artificial intelligence is stimulated using at least one random signal and/or using a quasi-linearity property for visual concepts and 1.3 the stimulated artificial intelligence generates at least one test data set that comprises image data and areas of action that are associated with the image data, and/or sensor data and areas of action that are associated with the sensor data, wherein in order to obtain the trained artificial intelligence that is provided in step 1.1, the following steps are implemented: 2.1 a learning data set is provided that comprises real image data that is recorded by means of at least one image capturing facility, and areas of action that are associated with the real image data, and/or real sensor data that is recorded by means of at least one sensor facility, and areas of action that are associated with the real sensor data, 2.2 an artificial intelligence is provided and 2.3 the artificial intelligence is conditioned using the learning data set that is provided. 2.1 a learning data set is provided that comprises real image data that is recorded by means of at least one image capturing facility, and areas of action that are associated with the real image data, and/or real sensor data that is recorded by means of at least one sensor facility, and areas of action that are associated with the real sensor data, 2.2 an artificial intelligence is provided and 2.3 the artificial intelligence is conditioned using the learning data set that is provided.