The 5 biggest data news stories of 2019
10 December 2019
Moore’s Law states that computing power doubles every two years. This means that the field of data science is constantly evolving as computers become more powerful.
As 2019 draws to a close we thought we’d take a look at some of the biggest headlines of the year concerning data.
1. The rise of the Citizen Data Scientist
As more free or cheap data analytics tools hit the market, and governments become better at proactively releasing big data sets the last few years have seen the emergence of the concept of the Citizen Data Scientist – essentially someone who does data science as a hobby or in their spare time, often without any formal training.
Gartner (who originally created the term Citizen Data Scientist back in 2016) is predicting that next year we will reach a tipping point – citizen data scientists will surpass data scientists in the amount of advanced analytics produced.
This opens huge questions around accuracy and the value of trained skills.
2. Google’s Quantum Computing breakthrough
This year saw a major advance in computer science that will quickly change the face of big data and analytics.
They reportedly achieved quantum supremacy – where a functional quantum computer was able to perform a task faster than any existing classical computer.
This proves that the theory behind a quantum computer is viable and will only spur on additional investment in this cutting-edge field.
The increased computing power available will mean increased collection of data and more powerful artificial intelligence to analyse it.
Quantum computing is on the way. And it will change the world.
3. Consumer data privacy improvements
The fallout from the 2018 Cambridge Analytica scandal continues. Consumers are more aware than ever of risks to their own data privacy – here in Australia over 2.5 million citizens opted out of the Federal Government’s My Health Record digital health system by the time of the close off period in February of this year.
Back in February OpenAI announced that they had developed an artificial intelligence algorithm so powerful at natural language processing that it was able to write believable fake news. In a world where social media is filled with fake news, many people found this understandably unnerving.
Over the course of the year they performed a staged release of the technology and by July had released the GPT2 algorithm in full.
OpenAI claim they so far they have seen “no strong evidence of misuse” – but if it is so good, then there may be no way of seeing how it is already being used to spread misinformation.
You can explore a demo of the algorithm here.
5. The Apple Credit Card and algorithmic bias
Tech entrepreneur David Heinemeier Hansson made global news with a series of tweets claiming that his Goldman Sachs backed Apple Credit Card gave him a credit limit 20 times greater than his wife, despite the fact that the couples file tax returns jointly.
The @AppleCard is such a fucking sexist program. My wife and I filed joint tax returns, live in a community-property state, and have been married for a long time. Yet Apple’s black box algorithm thinks I deserve 20x the credit limit she does. No appeals work.— DHH (@dhh) November 7, 2019
This opened the door to questions around algorithmic bias.
Goldman Sachs denied accusations of bias and offered to reevaluate credit limits on a case-by-case basis.
This leads to some big questions. Could a credit limit algorithm be sexist? How much transparency should there be on algorithms and the decisions they make.
Using AI & Machine Learning to make your work m...
04 December 2019
It’s easy to dismiss artificial intelligence and machine learning as just buzzwords, or technology that belongs in the distant future.
But that’s not the case. Here at The Red Fox Group we’re utilising advanced machine learning and artificial intelligence techniques to drive efficiencies for our customers, even in places where you might least expect it.
We’ve recently deployed a new version of the business card scanner in SwiftFox CRM which now utilises some very exciting cutting-edge features.
Optical Character Recognition is a technology that has been around for decades. Computers have long been able to read text and convert it to digitised information. We’ve taken that to a new level by partnering with Microsoft to utilise their Computer Vision cognitive service.
Computer Vision is OCR technology on steroids. It’s enhanced with machine learning models so SwiftFox can now make intelligent assumptions about the nature of objects and characters rather than just trying to map it using simple pattern recognition.
This gives it huge advantages. It can handle blurred text, extravagant fonts, and text at arbitrary angles – even upside down. It's much more accurate because of that. If you’re scanning a business card in real time at a cocktail function, or in the Uber on the way home, this will radically improve the accuracy of text recognition.
But that’s just the start.
Once we have captured the text out of an image of a business card we’re able to use machine learning text analysis to figure out how the data is structured and how it relates to our data models for people and organisations.
We get both Microsoft and Google’s cloud AI services (Microsoft Text Analytics and Google Cloud Natural Language) to analyse the grouped text structures and pass back which data fields each piece of text should map to, and how confident the artificial intelligence is of its finding.
SwiftFox then analyses the results of the two-machine learning models and uses the data that is most accurate to pre-populate data fields.
A very common problem with traditional business card scanning technology is that it has made a lot of assumptions about the text layout – eg most business cards have the person’s title directly after their name. But what if the business name comes after the person’s name? Or their job title comes first? We’re using machine learning to bypass assumptions and are getting far more accurate data back on what information is captured in each piece of text.
This means that when you’re loading a new contact through the business scanner, the chances are really good that we’ve correctly identified which parts of the business card go into the right part of the database. No more accidentally creating new organisations called ‘Managing Director’!
Hopefully this gives you a better idea of how we’re using advanced artificial intelligence and machine learning to make even simple tasks more efficient.
What Disney+ means for your business or organis...
27 November 2019
Why do you care about Walt Disney entering the subscription video on-demand streaming business with their new product Disney+?
Last week Disney+ launched around the world to massive fanfare. Despite some initial technical issues, their competitive prices and excellent catalogue have attracted huge interest. The Star Wars spin-off The Mandalorian alone has proven a massive draw card.
In the week following the Disney+ launch, Netflix app downloads grow 4% year-over-year. It’s early days but it seems there is still a lot of appetite out there for streaming content.
But what happens when consumers hit the wall? What happens when they check their bank balance and start to feel the hit from signing up to more and more subscription services?
Not only do they have to worry about multiple video on-demand services. Here in Australia it’s not unimaginable for someone to subscribe to Netflix, Stan, Disney+ and Kayo Sports. But you’ve now got more and more software moving to a software-as-a-service model (Office 365, Google Plus), common household products (Dollar Shave Club for razor blades, Three Thousand Thieves for coffee), even grocery shopping is moving towards subscription services.
In February 2018 McKinsey & Company found that subscription-based e-commerce had grown by more than 100% a year over the past five years. Surely that is only increasing.
There is a real risk of increased churn and decreasing customer loyalty as more and more purchases are made through subscription services. As the monthly subscription bill rises, consumers are likely to be more ruthless with cutting services that don’t meet their needs.
How is your organisation staying at the top of the subscription ladder?
Smart organisations are increasingly investing in retention or customer loyalty models – a predictive statistical model that takes your data points as inputs and gives every single one of your customers a score that indicates how likely they are to go elsewhere. You can even make a predictive model more powerful by integrating free and commercial external data sources.
Are you harnessing the power of the data you already have about your subscribers and customers? In an increasingly competitive subscription-based market, you can’t afford to not invest in using data to retain your customers.