As little as one can foresee a pandemic, or an economic crisis, or the onset of winter in December, excitement about one’s own person is just as unpredictable. What does the public know about the burdens and duties of a … Continue reading The Art of the Non-Apology
Some things have gone wrong in the European Union, others well, since the pandemic has taken hold of the world. But what has become clear for some months now is the degree of incompetence of the European authorities and local … Continue reading COVID: No, the EU is not ‘too nice’, it just doesn’t think in terms of ‘First Principles’.
Data bias caused by poorly curated data is increasingly emerging as an important issue in the development of artificial intelligence. To this end, it is important to know that today’s AI is fed millions and millions of data sets through machine learning. Where this data comes from, and who selects and compiles it, is critical. If such a data set, which is supposed to recognize faces, has predominantly faces with light skin color or more men than women, then such faces are recognized well, but the AI then makes more errors with women or dark-skinned people, or even in combination with the face recognition of dark-skinned women.
While this may not be so tragic in the case of facial recognition, in other systems it can be a matter of life and death, imprisonment or freedom, or the granting or denial of credit. Another pitfall is that human stereotypes are embedded and deepened in the system. One such case was discovered by Anna Kholina, a Russian living in Helsinki. She had Google Translate, an AI-based online translation software, translate some sentences from gender-neutral Finnish into English. The result reflected gender stereotypes. Sentences that the system associated with typically female activities were translated with the female case, and those with typically male activities were translated with the male case.
Such translations pose a problem when it comes to eradicating gender stereotypes. The fact that women are allowed to vote, study, and take up professions, and even roles that were only open to men until recently can now be exercised as a matter of course, is not self-evident and also has a lot to do with language and pointing out opportunities.
Continue reading “Gender Stereotyping in Google Translate”
An unassuming Twitter account featuring a pretty young lady who appeared to be a motorcycle enthusiast garnered a number of fans in Japan. She was repeatedly seen posing in front of the bike, standing in front of the sea with her motorcycle or tinkering with it in her workshop.
Until someone discovered some inconsistencies. For example, one picture showed an arm with a little too much hair, and in a mirror visible in a photo, another curious detail. The mirror image looked quite different from the young lady. Not only was the person a lot older, but also a man.
Continue reading “FaceApp and the cute motorbike girl”
In a TED Talk, robot ethicist Kate Darling of MIT describes how she demonstrated a small dinosaur robot to a friend. This little robot named Pleo had some sensors and motors built in, it could walk around and move its head, but it could also tell if it was standing upright or lying down. If he was lying down or hanging down, he would start crying. Darling’s friend examined the robot while holding it upside down, which caused the robot to cry. Darling felt so uncomfortable doing this that she took the robot back from her friend.
Her reaction to this, this pity for the dinosaur robot, which was ultimately nothing more than a toy, astonished her herself, and she asked herself why we form emotional connections with machines.
Darling’s reaction was not unusual; it happens to others. In P. W. Singer’s book ‘Wired for War‘, American soldiers speak of the ‘robo hospital’ rather than the ‘Joint Robotics Repair Facility’ where they send their drones and demining robots for repair. These same soldiers give their robots ‘funerals with full military honors.’ And last but not least, we already learned about the overturned Kiwibots that are immediately put back up by passers-by because they looked so ‘sad’. All this shows us that we humans are very quick to make such emotional connections. Everything that moves and looks like life can awaken our compassion.
Continue reading “How Do You Design A Lovable Robot?”