- They aren’t a “lump demographic”, they’re within an age bracket, but there are no specifics, just generalizations.
- Over 87% of Millennials prefer social media apps that are less public; they dislike the marketing messages in more open apps like Facebook.
- 59% of Millennials in our research indicate they mistrust over 90% of the news they get in their social media feeds.
- When it comes to personal information, contrary to general assumptions, over 62% don’t like to share personal details outside a closed group.
- Those aged 18-24 are more likely to be skeptical of unknown people attempting to be friends in apps like Snap or WhatsApp. But see Facebook and Instagram as more “open” platforms while sharing less information publicly.
- Over 76% of those aged 18-35 say a primary part of choosing a new app is that it has the ability to have private messaging.
- Over 56% of those aged 18-35 dislike the term “Millennial” and find it a derogatory term.
- Home automation tools like Amazon Echo or Nest aren’t really that interesting to them; largely because they don’t own houses and are highly urbanized and very much into “buying local” and a more social approach to shopping that is physical. Those aged 18-35 rarely have a house and don’t have as much disposable income either.
- They’re 60% more likely to buy small commodity items on a mobile than via a laptop/dekstop or some home automation device.
- Only about 12% of Millennials have an interest in wearables and tracking their fitness.
- Just over 43% of those aged 18-35 say they don’t look for apps outside those pre-installed on the device they buy (i.e. the Mail app on iPhone or Outlook on Windows.)
- 48% say they are looking to reduce the amount of technology in their daily lives.
- If Facebook is relying on AI to evaluate images, it shows just how bad Artificial Intelligence really is right now. All the AI Engine would have seen was a naked image…that’s what it was programmed to block, so it took the post down. This shows that AI is so very, very far from being good…since the AI system did not understand a) history b) relevance c) context d) emotion. Not much “intelligence” at work there. Facebook needs to train it’s AI algorithms better (and the folks writing those algorithms.)
- If Humans made the decision it shows that whomever is doing the hiring for editors at Facebook likely has a poor education and that the people they’re employing are even more poorly educated. Because they did not understand the historical significance of the photo. In addition, they were too daft to do any background research, like a simple drag and drop Google image search.
Only recently have we seen the conversation around the need for more women being involved in the development of Artificial Intelligence. I argue that it is absolutely vital to have input and full engagement with women at the most senior level of development in Artificial Intelligence. No, this isn’t a feminist argument, it is a logical deduction and scientifically sound.
Since the early days of conceiving of AI in the 1940’s, development has been driven by men. All of our dystopian and quasi-Utopian Hollywood iterations of what AI might be like are driven by the male perspective. While the voices used in the voice-enabled aspects of AI are dominantly female, the underlying development isn’t. I think this is a problem for the future of A.I.
Why We Need The Feminine in Artificial Intelligence
I explore, quickly and briefly, the primary reasons we need the feminine as a key element in AI development;
Humanity: As humans we are male and female (setting aside the gender fluidity issue for a moment.) Ideally, AI would be gender neutral, but that is unlikely to be possible. To achieve greater balance and include “nurture” and the feminine perspective of what it means to be “intelligent” then the feminine needs to be involved. It’s the only way for AI as it becomes more advanced, to be closer to humans.
The Economics: For AI to be successful, it will have to prove its economic value. If AI is not profitable, companies will stop development. For AI to be more economically successful, it must include the feminine perspective. A singular perspective will lead to failure in business opportunities and profitability.
Qualia: Though we may never achieve this with AI, it is still an important consideration in the development of AI systems. The feminine experience of certain qualia is likely different from the male. So we see where the feminine is needed here as well.
More Than Data: Using data alone will not inform truly progressive AI systems. Experiences and perspectives are needed to train AI’s. The feminine needs to be considered here as well, otherwise we are again creating a system with only one perspective. That is not intelligent.
There is Some Progress
This year a small group of women will meet who 11 years ago formed a group called WiML and they’ll be holding their 11th annual workshop this year, coinciding with the NIPS conference. But so far representation for women in AI remains largely in academic circles. Industry needs to step up. Yet as the tech industry tries to and the likes of Bill Gates try to push this issue, just attracting women into computer science is a challenge itself. There are also some very intelligent women who are participating in the larger philosophical questions around AI’s development. But not enough.
This is a short blog post attempting to posit a position in very short thoughts. While there is some progress, it is estimated that in the AI field, less than 14% of those engaged are women. This number needs to be much higher, but the tech industry is struggling just to attract women in the first place. AI may or may not become truly cognizant and aware and “beyond human”, but in case it does, we need to consider a lot of factors beyond just a “kill switch” and it may very well be that adding the feminine to AI at these early days may be what stops rogue AI’s from those dystopian futures that do so well at the box office.
Note: I consult at the senior executive level regarding Artificial Intelligence. My focus is on governance and risk issues, risk mitigation strategies, corporate strategy alignment and business case development.
What do you think?