What caught my attention this week

At our worst, we’re programmed to think only of ourselves. At our best, we consider the impact of our actions on others. Unfortunately, when we do consider others, it tends to be only of the people that look and think like us.

The beauty of the Internet and our devices is that it has exposed us all to people outside of our own circles. And I truly believe it has pushed us towards a better world.

However, there’s a massive looming threat.

The technology and algorithms shaping the next decade are encoded with many of the same biases that have plagued our past. Ultimately, we’re risking a reversal of the progress we’ve made.

This is a concept I’ve been thinking deeply about this week. The following video and articles address the landscape of the problem and pose a solution that could potentially work.

Our future must include a wide variety of people, abilities, and ideas. And for that, we all must tread outside of our own comfortable circles of like-minded people.

This is what caught my attention in technology:

Is AI Racist?

Artificial intelligence is being used to do many things from diagnosing cancer, stopping the deforestation of endangered rainforests, helping farmers in India with crop insurance, it helps you find the Fyre Fest Documentary on Netflix (or Hulu), or it can even be used to help you save
money on your energy bill.

But how could something so helpful be racist?

Watch the video below for my thoughts on this technology:

The Blind YouTubers Making the Internet Accessible

“I went to see Tropic Thunder and all the resolution was visual,” Edison says. “I’d spent two hours with these characters, and in the end, I had no idea what the heck had happened to them.” He turned that frustrating experience into a YouTube channel: the Blind Film Critic.

Read the entire article here

AI Is Sending People To Jail – And Getting It Wrong

Machine-learning algorithms use statistics to find patterns in data. So if you feed it historical crime data, it will pick out the patterns associated with crime. But those patterns are statistical correlations—nowhere near the same as causations. If an algorithm found, for example, that low income was correlated with high recidivism, it would leave you none the wiser about whether low income actually caused crime. But this is precisely what risk assessment tools do: they turn correlative insights into causal scoring mechanisms.

Read the rest of the story here

The People That Sell Millions Of Online Dating Profiles Could Solve AI’s Racism

AI is only as good as the data it learns from. And since a lot of the data sets out there today operate in biased territory, we’re getting biased AI. There’s a huge market opportunity for a company to build diverse data sets for developers to train their algorithms on. This sort of data brokering has been done before, but not with the level of polish and respect we would like to see.

For instance, USDate is a company that sells online dating profile data at massive scale to people that are looking to start their own online dating sites. It’s pretty shady, considering I can buy hundreds of thousands of data profiles for less than a hundred bucks in some cases. But this is a business model that could prove very beneficial to AI.

If you’re an Inevitable/Human member, read more on this theory here

The Automation of the Everyday Man by 2030

Drilling into demographics on the US workforce revealed who is most likely to be challenged by automation. On average, half of the tasks performed by workers aged 16 to 24 can be automated over the next couple of decades, the report says, compared with just 40 percent of the tasks of older workers. Hispanic workers are in jobs that are already 47 percent automatable; for Native American and black workers, those shares are 45 and 44 percent, respectively. For the average white worker, according to the study, only 40 percent of their job is within reach of machines in the next two decades.