Computer technology combined with advanced internet has given birth to modern day Artificial Intelligence (AI). Humans have since long strived for tech that could reduce their dependence on human labour. Computers were the first revolutionary technological advancement in a very long time that helped humans realize unimaginable feats. However, after the advent of AI, the possibility has been stretched too far now. Advanced AIs are capable of things that most humans cannot even comprehend let alone control it.
Artificial Intelligence is a machine’s intelligence that is inorganic in nature. It is different from human intelligence at least as of now. It is very goal oriented and can go to extreme lengths to accomplish its goal as programmed. This is the reason that scholars have warned that if the future AIs’ goals are not in line with that of the humans then it will be a chaotic situation.
AIs are being developed each day to improve their efficiency. However, it has been noticed that numerous biases have already seeped into them. The reason is the biases in the existing data.
An AI learns through a process called Machine learning. As compared to traditional computer technology, where a user needed to input all the commands for the computer to perform, an AI just needs the basic requirements and then it can figure out the rest on its own through machine learning. Machines can learn from the huge ocean of data already available in the world.
Through the help of the internet, AIs can roam across the knowledge corridors and information warehouses to learn as much as possible for smooth functioning. However, the problems that the modern scientists, researchers, technicians and other users are finding are the existing biases. The data from which the AIs are learning is already full of intentional or unintentional biases. These biases are based on gender differences, race, colour, economic inequality and so on. This creates a problem for the future as well because the AIs that are getting more powerful each day are boosting the existing biases.
AIs often confuse correlation with causation, which is not the correct method. As per Richard Freeman’s article in Medium, he describes the problems of AI’s analysis. AI can show a positive relationship between higher sales of ice cream on a beach with higher drowning rates. However, this is not correct as the high number of drowning is due to a higher number of swimmers. On the other hand, a higher sales of ice cream is also due to the higher number of people on the beach and due to the summer season. Here there is no relation between the sale of ice cream and drowning. These are the kind of problems AI is facing.
Women, for the longest time, have been away from the mainstream STEM fields. It seems that society as a whole has very biased against women and considered them not suited for the STEM fields. This thinking has somehow resulted in fewer women in technological fields and especially AI. It is estimated that only around 8% of the workforce in AI constitutes of women, whereas this percentage goes up to nearly 20% in computer sciences, which is not much as well.
AI needs more women participation for various reasons. AI has been developed by men and the gender biases seep in clearly. Women’s part of the story needs to be represented as well. Women tend to be more empathetic and caring than men. AIs of the future needs to learn empathy, care and other similar emotions too. Many scholars have predicted that AI has the ability to take control of the world from humans. This is why women are required in the field to make the AIs learn more about human emotions from the lens of a female. Compassion, empathy and care are crucial for the existence of society and AIs need to learn that apart from cold calculations and big data analysis. The huge loads of data will be of no use if not used for humanity’s benefit.
Women have contributed in a major way in every field of technology over the entire human history and we believe that they can too in the field of AI as well. It is high time that the society at large breaks the stigma and encourage women to be a major part of the mainstream STEM fields.