AI applications should respect and protect user privacy; decisions made by AI should be fair, unbiased and explainable to human beings; and for the purpose of accountability, responsibility attribution should be possible if something goes wrong.
Figuringout What is Right
With trade volumes being three times more than the nation’s Gross Domestic Product (GDP), revolutionising the way trade documents were processed held promise of great returns. Hence, it naturally became an area of focus for CrimsonLogic.
GettingBuy-into Best Practices
The Association for the Advancement of Arti cial Intelligence (AAAI) has also teamed up with the Association for Computing Machinery (ACM) in 2018 to organise the AAAI/ACM Conference on Arti cial Intelligence, Ethics, and Society (AIES)3. The Conference provides a platform for AI researchers and social scientists to come together and work out interdisciplinary solutions to ethical challenges in AI applications.
TakingPositive (Not Limiting) Actions
However, without waiting for ethical AI technologies to be ready, the legislative landscape has already evolved. In 2016, the European Union (EU) established one of the most stringent privacy protection laws targeting AI applications with the General Data Protection Regulation (GDPR). The GDPR speci es many terms aimed at protecting user privacy and prohibiting organisations from exchanging data without explicit user approval. Similar laws have also since emerged in China and the US. These harsh legal environments threaten to impede AI development by making it infeasible for different companies who own diverse types of user data to collaborate and build new business.
Pick an industry that provides you a runway to grow and where you envision you can work in for a long time to develop your expertise.
The Tech Industry, The Tech Professional
One of the biggest misperceptions about working in tech is that when one works in a tech role, one is automatically working in the “tech industry”. This is actually incorrect because “industry” is used to refer to companies and organisations. Some examples, banks and insurance companies are part of the finannancial services industry; airlines and taxi companies are part of the transportation industry. Hence, by that definition, the ones that make up the tech industry are actually hardware, software and IT services companies.
Flying Solo, Flying in Formation
It is not uncommon for the media to portray programmers as lone wolves (usually male) who hide in their favourite corner of the house, code non-stop for x hours, and then emerge with a program that changes the world.
This cannot be further from the real world. Tech work is really more like playing team sports. Everyone plays to their best in the respective functions, but the game can only be won when everyone works seamlessly as a team. Today’s business and IT operating environments are pretty much like the fields and the courts (with aircon of course!). Not only are ideas and plans brainstormed and discussed, bugs are also tackled – as a team.
Working with People, Working with Machines
If you think working in tech is to work (almost) exclusively with machines, then you are sorely mistaken. Yes, there’ll still be a lot of “face time” with machines: translating requirements into code, analysing data produced, optimising response time, replicating errors reported by users to x that elusive bug. Or in the case of administrators, to monitor the machine making sure it’s operating optimally, and with no unwanted guests in the system.