AI is the ‘new electricity’ – but it needs us all as engineers
If AI is to be fully harnessed to create a better world, it’s going to require a matching workforce that doesn’t currently exist, and new schemas of ethics and education that haven’t yet been drafted.
When considering the practical application of AI in today’s society, perhaps the most pressing question is this: if AI is “the new electricity”, then where are all the electrical engineers?
According to recruitment firm Jobsite, the number of vacancies related to AI, automation and machine learning increased by nearly thirty percent between and 2015 and 2016 – a figure that’s expected to continue rising.
In business, many companies are lagging behind technological advancement. Research conducted by Mckinsey & Co found that 28% of firms don’t feel that they have the technical capabilities to implement AI.
“Demand for deep learning vastly outstrips supply”, said ex-Baidu chief scientist Andrew Ng in a recent interview with Techcrunch. “It’s concentrated in a few labs and a few universities.”
Making AI accessible
For all the talk of AI’s potential to collect and democratise knowledge, first the technology itself has to be democratised.
Major AI proponents are realising the value in making this happen. Microsoft has vowed to “take it from the ivory tower and make it accessible to all.” And Google CEO Sundar Pichai earlier this year announced Google.ai, an initiative that aims to “bring the benefits of AI to everyone” via the new site, which will act as a hub for new AI research.
The accessibility of such schemes is important. From the enigmatic workings of deep learning to the omnipotence of Big Data, technological progress can often leave the layperson feeling overawed, intimidated, and excluded (quite literally in some cases, as with the Facebook chatbots that recently began developing their own secret language). Dispensing knowledge about AI in plain terms, rather than double-dutch tech-speak, is surely the most practical way to encourage more businesses to adapt.
Though our technology is cutting edge, learning how to use Rainbird is far from rocket science. Using open source architecture and the easy-to-understand RBLang code, the platform’s reasoning is visualised in two tabs: one for the knowledge map, and one for the code. If the user writes the code first, the concurrent knowledge map will automatically form in the other tab, and vice versa. It’s a completely intuitive process.
From the top down
This process of encoding expert knowledge into our platform is what we call human-down AI. Unlike machine learning – or bottom-up AI – which can leave users in the dark with its black box approach, Rainbird follows a rules-based approach, which is all the easier to comprehend due to its grounding in human logic.
Rainbird is designed more for use by business people than developers – that could be a lawyer who still uses a flip phone, or a hedge fund manager who hasn’t even heard of coding. The essence of this versatile platform is that it can theoretically be used and understood by just about anyone. Without the need for specialist IT skills, experts can encode their own logic into Rainbird.
The resulting benefits for customers everywhere are boundless. From consultative chatbots to tailored financial products, human-down AI has the potential to make everyone’s life easier.
The learning curve
Let’s return to the electrical analogy for a moment. For at least a century after its discovery, electricity tended to be confined to the elite and the scientifically minded. Eventually, it became the unanimously transformative tool that it is today due to its dissemination – more people learned how to make use of it, and more consumers benefitted as a result. To quote the CTO of TOPBOTS Mariya Yao, “entrepreneurs and engineers around the world see machine intelligence as a path towards a better society.”
Rainbird aims to be a part of this process. Not only is Rainbird human-down vs data-up, but each company that partners with Rainbird can undergo full training via the Rainbird University programme, so that our product not only helps users, but also teaches them. Our Vimeo channel aims to do the same: there are outlines of the history and future of AI, an overview of cognitive reasoning, and explanations of Rainbird’s practical use in business. And to encourage innovation even further, the Rainbird platform is discounted for universities, social venture projects and SMEs.
The future of industry rests on harnessing AI-powered solutions, and at Rainbird we believe that anyone can become an engineer of the ‘new electricity’.