Prior to the era of Artificial Intelligence, humans would collaborate on decisions. As the saying goes, "two brains are better than one." But with advancements in AI, screening data and ideas has been made easier and more efficient. Its impact on the economy and its implications regarding the future of the workforce has ignited a fierce debate that has been contributed to by everyone from Silicon Valley to the White House. Of course there are naysayers, like Nick Bostrom, who warns that AI could quickly turn dark and dispose of humans altogether, saying, "The subsequent world would harbor economic miracles and technological awesomeness, with nobody there to benefit."

MogIA, an artificial intelligence (AI) system developed by an Indian start-up, correctly predicted the outcome of this year's elections. It based its analysis on 20 million data points from platforms such as Google, Twitter, and YouTube, reviewing public engagement across various posts in relation to individual candidates. Earlier this year, an AI system was able to accurately predict the winners of the Kentucky Derby. In October, a study reported that AI can already predict the outcomes of cases at the European Court of Human Rights with a 79% accuracy. Leading up to the historic election, Democratic candidate Hillary Clinton led the late polls with a small, but consistent lead.

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Few industries are as competitive as ecommerce. Not only are online retailers competing with other online stores and brick-and-mortar locations, but also the overall noise that is the Internet. We live in a world where consumer attention span is getting shorter and shorter: 40 percent of people abandon a website that takes more than three seconds to load, and the average shopping cart is abandoned more than 68 percent of the time. I'm hard pressed to find an ecommerce site that is not constantly scrambling to engage more and drive more sales. Technology is finally helping with those efforts in a big way.

This story is part of a series inspired by the subjects and speakers appearing at BBC Future's World-Changing Ideas Summit in Sydney on 15 November. If you believe some AI-watchers, we are racing towards the Singularity – a point at which artificial intelligence outstrips our own and machines go on to improve themselves at an exponential rate. If that happens – and it's a big if – what will become of us? In the last few years, several high-profile voices, from Stephen Hawking to Elon Musk and Bill Gates have warned that we should be more concerned about possible dangerous outcomes of supersmart AI. And they've put their money where their mouth is: Musk is among several billionaire backers of OpenAI, an orgnisation dedicated to developing AI that will benefit humanity.

Mark Zuckerberg and his wife, Priscilla Chan, have laid out plans to invest $3bn over the next 10 years with the not insignificant goal of tackling all diseases. "Can we cure, prevent or manage all disease by the end of this century?" The Chan Zuckerberg Initiative will focus on some of the world's biggest killers, including heart disease, cancer, infectious diseases and neurological diseases. One of its biggest investments is to be a $600m "Biohub" at UCSF, which will bring together scientists and engineers from Stanford, Berkeley and UCSF – who haven't collaborated in this way before – to develop tools to treat diseases. The second focus will be transformative technology, all of which will be made available to all scientists everywhere. "Throughout the history of science, most of the major scientific breakthroughs have been preceded by some new tool and technology that allows you to see in new ways," explained Zuckerberg.

It has been said that to give a man a fish is to feed him for a day, whereas to teach a man to fish is to feed him for life. Forward-looking financial service companies are similarly finding that giving computers instructions is not nearly as fruitful as teaching them to write their own. From assessing credit risks to beefing-up the security of their own networks, fintech startups, in particular, are turning to machine learning finance-based solutions in order to work smarter rather than harder. Considering that over 200 leading financial institutions will attend the upcoming October 2016 Machine Learning Fintech Conference, investment in this subset of artificial intelligence (AI) seems to be a wise move, indeed, for companies that don't want to be left behind. With leading banks starting to invest in AI, and machine learning in particular, fintech companies will be significantly disadvantaged if they fail to do likewise.

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Tech giant Google is teaming up with gaming publisher Blizzard to improve artificial intelligence (AI) through one of its games: StarCraft. However, it seems other games may fit the "teaching" bill as well. According to Google, Blizzard announced in the annual BlizzCon that it will release tools that will allow third parties to teach AI how to play their hit game StarCraft 2. This is in collaboration with Google's DeepMind project, and the tools will be using the DeepMind platform. The DeepMind team said StarCraft is an "interesting platform" to develop current research on AI. The gameplay itself may be a useful environment to simulate the "messiness" of the real world.

IBM's Watson system will help doctors diagnose rare illness faster by scanning through huge medical records to pull out relevant information. "We don't need more physicians, we need more IT power." It's a controversial statement for anyone with an interest in healthcare to make, let alone for a senior doctor heading up a centre for rare and undiagnosed diseases. But Dr Jürgen Schäfer, in charge of tackling the most mysterious conditions that arrive at the centre in the University Hospital in the German town of Marburg, is used to solving seemingly intractable problems. But now, rather than identifying the illnesses that have baffled numerous doctors before him, Schäfer - sometimes called the German'Dr House' -- has worked out how to crack another tricky medical problem: how to treat a spiralling number of patients, each with a lengthy and complex health history, without employing a whole new team of doctors.