Tag: government

Implementations of Trustworthy and Ethical AI (Report)

Implementations of Trustworthy and Ethical AI (Report)

Want to consider artificial intelligence applications and implementations from an ethical standpoint? Here’s a high-level conceptual view you might like:

Kolja Verhage wrote a report The Implementation of Trustworthy/Ethical AI in the US and Canada in cooperation with the Netherlands Innovation Attaché Network. Based on numerous interviews with AI ethics experts, Kolja presents an overview of approaches and models on how to implement ethical AI.

For over 30 years there has been academic research on ethics and technology. Over the past five years, however, we’ve seen an acceleration in the impact of algorithms on society. This has led both companies
and governments across the world to think about how to govern these algorithms and control their impact on society. The first step of this has been for companies and governments to present abstract high-level principles of what they consider “Ethical AI”.

Kolja Verhage

You can access the report here.

Building a $86 million car theft AI in 57 lines of JavaScript

Building a $86 million car theft AI in 57 lines of JavaScript

Tait Brown was annoyed at the Victoria Police who had spent $86 million Australian dollars on developing the BlueNet system which basically consists of an license-plate OCR which crosschecks against a car theft database.

Tait was so disgruntled as he thought he could easily replicate this system without spending millions and millions of tax dollars. And so he did. In only 57 lines of JavaScript, though, to be honest, there are many more lines of code hidden away in abstraction and APIs…

Anyway, he built a system that can identify license plates, read them, and should be able to cross check them with a criminal database.

Via Medium

I really liked reading about this project, so please do so if you’re curious via the links below:

Part 1: How I replicated an $86 million project in 57 lines of code

Part 2: Remember the $86 million license plate scanner I replicated?

Part X: the code on Github

Cover image via Medium via Freepik

Where to look for your next job? An Interactive Map of the US Job Market

Where to look for your next job? An Interactive Map of the US Job Market

The people at Predictive Talent, Inc. took a sample of 23.4 million job postings from 5,200+ job boards and 1,800+ cities around the US.  They classified these jobs using the BLS Standard Occupational Classification tree and identified their primary work locations, primary job roles, estimated salaries, and 17 other job search-related characteristics. Next, they calculated five metrics for each role and city in order to identify the 123 biggest job shortages in the US:

  • Monthly Demand (#): How many people are companies hiring every month? This is simply the number of unique jobs posted every month.
  • Unmet Demand (%): What percentage of jobs did companies have a hard time filling? Details aside, basically, if a company re-posts the same job every week for 6 weeks, one may assume that they couldn’t find someone for the first 5 weeks.
  • Salary ($): What’s the estimated salary for these jobs near this city? Using 145,000+ data points from the federal government and proprietary sources, along with salary information parsed from jobs themselves, they estimated the median salary for similar jobs within 100 miles of the city.
  • Delight (#): On a scale of 1 (least) to 10 (most delight), how easy should the job search be for the average job-seeker? This is basically the opposite of Agony.

The end result is this amazing map of the job market in the U.S, which you can interactively explore here to see where you could best start your next job hunt.