It’s likely no surprise that women are still massively underrepresented in the tech industry today. Even with a push over the last few years for more women to pursue careers in STEM—science, technology, engineering, and mathematics—they still make up a tiny percentage of those working in the field. Data shows that of those doing STEM-focused research around the world, less than 30% are women.
Unfortunately, when you narrow the focus down to women working specifically in smart tech and machine learning, the numbers get even smaller. You might wonder why it matters who is behind the data and code creation when it’s essentially a non-gendered machine or robot doing all of the processing, but it does. Machines aren’t inherently biased, but humans are, and when humans are teaching machines how to learn and what to do, our biases naturally become part of the code.
Our computers, phones, and any other smart devices that we use today utilize technology that mimics our thought and decision-making processes. So if the majority of people working with smart tech such as artificial intelligence are men, then anything that utilizes AI will skew towards the male perspective.
What Is AI and How Are We Using It Today?
Though artificial intelligence might bring to mind images of a future world run by robot overlords, it is far less ominous and science fiction-like than that. AI is already a part of so many things that we use and interact with daily—it’s not the future—it’s the present.
Though artificial intelligence sounds like a far-fetched term, it is basically the use of algorithms in computer systems to mimic how humans process information, and the more input it receives, the smarter it gets. It’s not just a part of our personal devices either; businesses are using AI to improve customer service and interpret data to further develop their systems and run more efficiently.
Google is even leveraging the power of AI to create tools to enhance healthcare and help conservationists and scientists save endangered species and preserve indigenous languages. There is no end to the way we can harness the usefulness of AI. We can apply it to numerous situations to advance our capabilities and solve complex real-world problems.
How Will Artificial Intelligence Shape Our Future?
Artificial intelligence and deep learning systems are not just likely to change our future; it is already quite evident that they will and are already doing so. As humans, we are limited by our own minds and capabilities. There is only so much we can do—but AI and deep learning machines will allow us to scale our potential and complete tasks, projects, and missions that we would otherwise not be able to do.
Deep learning refers to systems with more advanced neural networks that can actually draw conclusions from the input it receives and adapt to changes. In contrast, some more basic and earlier forms of AI machines can only do what they are specifically taught to do.
Some examples of deep learning applications include:
- Facial recognition software
- Sound recognition software
- Natural language processing systems
- Systems that offer recommendations based on user interaction
- Video game AI
So how will deep learning and other advanced forms of AI affect our future? The simple answer is that it will make everything easier and more efficient. As mentioned above, as humans, we can only do so much. We should continue to maintain a human presence and interactions within our business operations—people still need that human touch. But when it comes to interpreting data and solving complex equations to optimise our systems and make new advancements, we need the help of AI.
Why Women Are Essential to AI Research
Several industries can benefit from having more women, but especially those specifically handling the development and research of machine learning systems. AI is already an integral part of our society and nearly all industries. Our economy and its infrastructure run on many systems that use AI every day. The problem is, that when these systems are all designed primarily by men, the processes that the computers use to learn and interpret data will result in a skewed outcome.
Mark Minevich, a contributor to Forbes.com, writes, “—organisations will always fail to harness the fullest capacity of their digital innovations without including women, as machine learning technologies will be fed a constant stream of biased data, producing junk results that are not reflective of the full picture, causing potentially catastrophic harm to organisations.” And he’s right. If AI is becoming a significant part of our society and infrastructure, and women will undoubtedly continue to be a part of this society, we need to include them in the research and development of these systems.
From transportation and education to media, customer service, and healthcare and wellness—industries are increasingly integrating artificial intelligence into their systems. Without more representation of women, the data these industries work off of and use to improve their operations will be deeply inaccurate. We don’t just need more women researching AI; we must have them. Continuing to leave them out is not an option. It is vital to the growth and success of AI itself and our growth as a society, and our ability to advance.
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