If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Understanding how my GPS works doesn't prevent it from degrading my map reading skills. Any skill you don't practice gets rusty. As Dunning-Kruger tells us, the more sure we are about our understanding the less understanding we are likely to have. AI that tells us what we already think to be true may well be simply crystallizing our biases in a non-disputable form. For example there was an article a few months back in Technology Review about using AI to (a) decide which convicted criminals to incarcerate based on an AI-generated "recidivism score", and (b) the use of AI to direct police to places where crime is most likely.
When we create our machine learning models, a common task that falls on us is how to tune them. People end up taking different manual approaches. Some of them work, and some don't, and a lot of time is spent in anticipation and running the code again and again. So that brings us to the quintessential question: Can we automate this process? A while back, I was working on an in-class competition from the "How to win a data science competition" Coursera course.
Interest in data science has risen remarkably in the last five years. And while there are many programming languages suited for data science and machine learning, Python is the most popular. Scikit-Learn is a Python module for machine learning built on top of SciPy and NumPy. David Cournapeau started it as a Google Summer of Code project. Since then, it's grown to over 20,000 commits and more than 90 releases.
People are generally afraid of AI, which is using computational statistics to make predictions. "71% of consumers fear AI will infringe on their privacy." A survey of Americans' thoughts on the impact of AI conducted by Oxford concluded this: "34 percent of respondents thought it would be negative, with 12 percent going for the option'very bad, possibly human extinction.'" Further, 18% were uncertain of the impact of AI, meaning that 64% of people have a negative or uncertain view of AI. However, as reasonable as some of these concerns might be, they're more reminiscent of fear of the unknown and the new, rather than problems with AI itself.
I lead the technology industry business unit for a fast-growing analytics firm. And one of the perks of my job is the numerous conversations I get to have with a variety of prospects or clients. I recently read the book'The Art of Thinking Clearly' by Rolf Dobelli, which deals with systematic cognitive errors of human beings as a result of our evolution. I enjoyed reading the book immensely, relating those cognitive errors to what I experience every day. I am selecting a few rampant cognitive errors mentioned in the book and linking them to situations I have come across.
As AI algorithms play a bigger role in decision making, how do qualities like ethics, compassion, and inclusion get programmed into the code? On this edition of Bytemarks Café, a talk about the gathering of thought leaders in Hawai'i to discuss how to move the technology agenda. The event is called TechForce 2019, and its aim is to bring together leaders from key sectors to accelerate tech readiness in our islands. On this edition of Bytemarks Café, a discussion about a novel new project that projects a 3D hologram from Hawaii to American Samoa. The project is called Holo Campus, and is the delivery of University of Hawai'i lectures over the trans-Pacific fiber optic broadband network to the Pacific Islands.
Anadolu Agency called on other European news media organizations to be more sensitive towards the ongoing tragedy in Syria. A three-day general assembly of the European Alliance of News Agencies (EANA) came to an end on Friday in the Czech capital Prague. Anadolu Agency editor-in-chief Metin Mutanoglu said in a speech that Syria's northwestern Idlib area was under heavy fire by Bashar al-Assad regime forces and that the region was facing a fresh wave of migrants. Mutanoglu underlined that though tens of thousands were forced to leave their homes due to regime attacks, the European news media were not interested enough in the issue. A new migration wave would affect not only Turkey but the rest of Europe as well, he stressed, adding that EANA should thus make a greater effort to draw attention to the humanitarian crisis in war-torn country .
Companies have learned the hard way that their artificial intelligence tools have unforeseen outputs, like Amazon's (AMZN) favoring men's resumes over women's or Uber's disabling the user accounts of transgender drivers. When not astutely overseen by human intelligence, deploying AI can often bend into an unseemly rainbow of discriminatory qualities like ageism, sexism, and racism. That's because biases unnoticed in the input data can become amplified in the outputs. Another underappreciated hazard is the potential for AI to cater to our established preferences. You can see that in apps that manage everything from sources of journalism to new music and prospective romance.
As a young child, I used to imagine what life would be like if I had a chauffeur to drive me wherever and whenever I wanted. Of course, this was a luxury afforded by only the wealthy and remained well out of reach for most people -- myself included. Fast forward to today, and the rise of the ride-sharing economy has essentially leveled the playing field, giving everyone affordable access to on-demand transportation. Access to artificial intelligence (AI) is poised to undergo a similar shift. Traditionally, large corporations and government entities have been ahead of the adoption curve because they've had the capital to invest in and the talent to leverage the technology.
I've never been one for Instagram. I'm incredibly cynical of everyone and everything, I tend to take pleasure in the misfortune of others, and I rarely post anything myself – so Twitter suits me down to the ground. However, I happened to find myself recently on Instagram, scanning through endless posts about travel and food, when I came across an advert for a clothing service, one that helps you pick a style and a full wardrobe to match. This is one I've seen a few times now, helped in no small part by the fact that every fourth post on Instagram seems to be reserved for adverts – let's face it, it's a platform for e-commerce as much as it is a social media. What's unusual about this clothing service is that it produces its recommendations using an algorithm.