CDAO Conference Melbourne 2019 – Data Commercialization Panel

The recent Cognitivo-sponsored CDAO Melbourne 2019 conference has come to an end. We had a great time meeting the speakers and vendors and engaging in deep conversations about data, privacy and emerging AI technologies.

We also had the privilege of hosting a distinguished panel with our partners and clients leading a discussion around data commercialization and privacy. Alan Hsiao, our Managing Director, was on hand to lead the conversation.

The Panelists

Jade Clark – Director of Data Partnerships at Westpac and a passionate explorer of ways data can be used to solve societal problems.

Paul Weingarth – Co-founder of Slyp, a data-driven e-Receipting fintech which just closed a funding round with three of the four major Australian banks.

Toby Johnston – a veteran Chief Data officer working at organizations like Commonwealth Bank, ASB Bank and currently Optus.

Paul Tyler – a long time research engineer and expert in all things privacy who currently serves as Data Privacy Lead at CSIRO’s Data61

Benjamin Szymkow – CTO at Cognitivo and Country Lead for OpenMined, an expert in current and emerging data privacy-preserving techniques

The Conversation

1)      Is there a level playing field between digital innovators, such as Google, and more traditional companies which provide vital services, such as banks and telcos, in the way they can exploit data to enhance operations and generate new revenue streams?

It was discussed that there are industry specific restrictions that the likes of Google, Amazon etc. are not subject to, for example the Telecommunications Act. These laws do create restrictions in addition to other legislative obligations, such as privacy, which all companies are subject to. It was noted that the challenge for firms providing essential services is to understand the specific data use cases that could be done within these constraints, among the very large spectrum of possible cases, and how that use case might be valuable to the customer and the business.

An example was the potential to use data for population movement trends, which is not about individuals and their data. Using population data to determine where to put more cell towers, thereby providing better customer experience and coverage, can also help to optimise company investment decisions. This use case is an example of finding an opportunity that hits the sweet spot for benefiting both customers and companies.

The panel noted that changing customer expectations and the potential for legislation changes to reflect various types of customer data rights is likely to see companies needing to receive express permission from customers to use data in certain ways in the future, which will level the playing field somewhat. It will no longer be enough for companies to simply disclose the general nature of how they use data, they will be restricted to certain approvals received.

2)      Given that we can never 100% guarantee that any data we hold is safe, what level of information security can we expect from data-driven organisations?

“The application of tools for assessing and quantifying privacy risk in data is vital in the modern era. We not only need to worry about security in terms of databases being breached or leaked in some way, but aggregated and de-identified data and even AI models themselves could leak data. Understanding and managing this risk is something CSIRO’s Data61 has been researching and the organisation is continuing to drive research in this field.” 

-          Paul Tyler

3)      What are the latest technological developments which are helping organisations in their quest to exploit data commercialisation opportunities, without unleashing significant new sources of risk?

 “Working with OpenMined, we focus on three of the most promising privacy-preserving techniques - Differential privacy, federated learning and secure multi-party compute.

Differential privacy is a technique that provides a mathematical guarantee of individual privacy. It means that we can perform analytical activities over a private data set, learn aggregate behaviours of individuals whilst maintaining ther privacy.

Federated learning is a technique which flips the need to move all data into a single location before we perfom any compute heavy training. Instead we bring our model to the data, training it on mobile phones, websites and edge devices without individuals’ private data ever leaving.

Secure multi-party computation is a technique that moves the cryptographic burden from compute to the network. It is a protocol that enables multiple organizations to collaborate with their own private data sets, supporting their own data governance models. It means organizations can keep their inputs to joint computation efforts private.

These techniques can be applied in combination to develop enhanced analytical insights and models, without increasing the level of data risk.”

-          Benjamin Szymkow

The debate continued to build on the idea that value creation and risk management go hand in hand. Provoked by the argument that “A silo-ed organisation is a non-competitive organisation – data is a driver of both value and risk”, Paul Weingarth and Jade Clark reminded the audience that an organisation is nothing without customer trust. Slyp and Westpac both see the opportunities of data commercialisation with a focus on value for the customer. This means activities need to be based on a foundation of consumer consent and transparent frameworks focused on allowable and non-allowable behaviours.

Around the conference, the topic of GDPR and how this applies to Australian companies was frequently discussed. The issue of whether AI models can be developed in a way which overcomes human biases – or if the biases inherent to the datasets resulting from human decision making condemn the algorithms to only be as good as the people who train them – was also a topic of debate.

Keynote speakers emphasised the cost saving and value creation potential of cutting-edge data strategy in the public service (e.g. at the Australian Taxation Office), in sports (e.g. the data-driven transformation of the Formula1 brand), for non-profit organisations (e.g. how the Heart Foundation is improving heart attack survivors’ information and motivation to act on it) and in business (e.g. how is increasing its level of service, whilst reducing the cost).  

We look forward to participating in the conference again in future and of course, to continuing to help our clients tackle these problems in their day-to-day business.