Discussion paper 1: Promoting trust and confidence
Summary
This is the first of 3 discussion papers that the province will release as part of its consultations to develop the Data Strategy. This paper aims to start a conversation about how the province should promote public trust and confidence in Ontario’s data economy, by posing questions for public discussion. Comments on this discussion paper will be collected until September 6, 2019 (Commenting is now closed).
The development of the Ontario Data Strategy is a great opportunity to leverage the potential of data in ways that benefit businesses and Ontarians. The Discussion Papers are a chance to begin a very important conversation with the people of Ontario, and represents an opportunity to be transparent about how this government thinks about data. We need all voices to address the issues and take advantage of opportunities in this data-driven world. We are excited to hear from you, as you help us develop a data strategy that promotes trust and confidence, creates economic benefit, and allows for a better, smarter government. Hon. Lisa M. Thompson Minister of Government and Consumer Services
Data is a valuable resource helping to drive innovation with the potential to dramatically improve goods and services for Ontarians. How we collect it, effectively use it, and prevent abuses of it are among the key policy questions of our time. The Minister’s Digital and Data Task Force will tackle these questions head-on, and we want you to join the discussion. In the end, it is our collective efforts as the people and businesses of Ontario, working with the rest of the country, to ensure a cohesive and comprehensive approach, allowing our province to thrive in a data-driven economy. Ms. Linda Mantia, Chair of the Minister’s Digital and Data Task Force
Introduction
More data is now being created in a single year than throughout the entire course of human history. Digital sensors are being embedded everywhere: in our homes, public places, and workplaces. Billions of people are increasingly participating in social and economic life through globally networked and integrated digital platforms. We are in the midst of a data revolution that is being powered by the Internet, increased accessibility to digital devices, and technological breakthroughs that have impacted more aspects of everyday life. Whether using smartphones, social media, search engines or interacting with machines, virtually every Ontarian is now producing data every second of their digital lives.
Individuals and machines are generating data at an unprecedented rate. Data has been referred to as “the new oil” and, conversely, the “new plutonium”,
However, recent events have highlighted the downsides of the new data-rich world. Reports of data breaches, data-driven manipulation, excessive surveillance and other data-driven threats are increasingly commonplace. As a result, the public is becoming increasingly concerned about the possible negative effects of technology and data on themselves, their families, and on the broader society and economy.
This paper will describe these trends and why provincial action is needed – in the form of a made-in-Ontario Data Strategy. The three pillars of the strategy are mutually interdependent. They are:
- Promoting Trust and Confidence: Introducing world-leading, best-in-class protections that benefits the public and ensures public trust and confidence in the data economy.
- Creating Economic Benefit: Enabling Ontario firms to develop data-driven business models and leverage the commercial value of data.
- Enabling Better, Smarter Government: Unlocking the value of government data by building the data skills and capabilities of public sector employees and promoting the use of data-driven technologies to ultimately serve Ontarians better.
For the purposes of Ontario’s Data Strategy, we have defined data broadly as “all structured information” in formats that are both digital and non-digital. There are many conceptions and definitions of data, which can be described along many dimensions, including format, quality, or controllership. Five types of data relevant to the Data Strategy are described below:
Government & public sector data
Data collected, produced or shared by government, such as:
- Open data
- Transit data
- Administrative data
- Statistical data
- Research and survey data
- Other types of operational data
Personal data
Data collected from, produced or shared by individuals, such as:
- Personally identifiable data
- Behavioural data
- Expressive data
- Biometric data
- Financial data
Business data
Data collected, produced or shared by businesses, such as:
- Operational and financial data
- Market research data
- Customer data
- Machine data
Derivative data
Data that has been processed, derived or transformed, such as:
- Anonymized data
- Linked data
- Predictions or inferences derived from data
In the case of the first pillar, addressing the public’s concerns about data-driven practices is critical to upholding the social license for their use. Through this pillar of the strategy, we aim to examine the negative impacts of data, institute best-in-class protections, and promote the ethical and responsible uses of data-driven technologies.
Key issues & context
As we become more reliant on the benefits of digital technologies and data, we encounter different challenges and new risks. This requires government, businesses, and individuals to find new and agile ways to ensure consumer protection, while as a society we reap the benefits. Without a whole-of-government data strategy, Ontarians remain vulnerable to the various applications of data-driven technologies. This is why the Government of Ontario has identified promoting trust and confidence in Ontario’s data economy as the first pillar.
Examples of threats and risks of data-driven practices
Data breaches, theft and misuse
A data breach occurs when the loss of integrity of an information system leads to unauthorized access to or disclosure of data and information. The prevalence, frequency and impact of data breaches are on the rise. For example:
- 2017: Security breach of Equifax, a credit reporting agency, exposes personal data of 143 million customers, including 19,000 Canadians.
- 2018: Facebook reports that in 2016 Cambridge Analytica and AggregateIQ used data harvested from 87 million Facebook users to influence election campaigns.
- 2019: CBC News reports that the data of 2.9 million members of Caisse Desjardins, including 173,000 businesses, was shared as a result of a breach caused by an employee.
Bias and discrimination
Data-driven technologies and practices can reinforce biases that exclude or single out certain groups of people or reinforce existing trends. The ‘black box’ of many automated decision-making systems can make it difficult to detect and combat these impacts.
- An algorithm used to make an administrative decision assigns undue weight to a characteristic leading to discrimination against a certain group (e.g., an algorithm which flags tax filers at risk of non-compliance could unfairly target smaller businesses owing to their small size).
- A machine learning algorithm optimizes for numerically dominant groups in a training dataset, excluding data at the margins which represent a marginalized group (e.g., a speech recognition algorithm could fail to recognize individuals with speech impediments).
Behavioural manipulation
Data generated by digital products and services about users’ characteristics, behaviour, interactions, can be used to affect users’ behavior in ways that may ultimately be harmful. For example:
- Algorithms are often a ‘blackbox’, with neither users nor regulators having a sightline into how recommendations are made. It is possible that algorithms can manipulate user behaviour, directing them towards dangerous or harmful content or choices.
- So-called ‘dark patterns’ use deceptive user interfaces and exploit information asymmetries to encourage users to unknowingly share data and personal information, or buy products and services.
Surveillance and loss of privacy
Surveillance in public places, the home, and the workplaces can compromise individual’s right to privacy and can infringe on people’s ability to communicate, organize and associate freely. In part, this decrease in privacy is driven by a desire for convenience and added safety in our day-to-day life and commercial imperatives to monetize and exchange personal data. These trends have created a range of risks; for example:
- Use of facial recognition technology, cellular signal interception, or automatic tracking by GPS-enabled devices can significantly reduce or effectively eliminate privacy about individuals’ whereabouts.
- Many smart home devices suffer from security vulnerabilities, and can capture and transmit sensitive personal information which may be vulnerable to monitoring and misuse (e.g., interception of audio and video feeds).
footnote 5
As more pieces of Ontarians’ lives shift online, determining the impact of these issues and implementing appropriate safeguards must be a priority for businesses and the government. Virtually every sector is affected by digital and data-driven trends. These sector trends, examples of which are provided below, present opportunities to increase efficiency, improve decision-making, and better allocate resources. But these trends also present challenges to navigate and manage, while they put new pressures on existing laws, policies and programs.
Examples of digital and data trends in key sectors
Health: Digital health tools – such as wearable devices and related services – are increasing the ability of individuals to monitor and manage their own health
Digital platforms and service providers: Growth of ‘platform monopolies’ where overwhelming power of dominant players – given data hoarding and network effects, for example – present barriers to entry for competitors
Public safety: New and growing digital threats to individuals, businesses and critical infrastructure including data theft, breaches, and cyber attacks
Public service delivery: Growing use of automated decision-making and decision-support systems to increase speed and efficiency of administrative decisions (e.g., determining social program eligibility)
Opportunities to promote ethical and responsible use of technology
It is in the public interest to instill trust and confidence in Ontario’s data economy. A loss of trust reduces people’s willingness to share data or give social license for its use. Likewise, diminishing confidence impedes the creative risk-taking at the heart of experimentation, innovation and investment. A loss of trust would, in turn limit the social and economic benefits arising from data. Just as in the economy at large, trust and confidence in the data economy are public goods which can be degraded if not actively upheld.
Government and the public sector play a significant role in upholding public trust in the data economy: As a key user of technology and steward of the public’s data, the public sector can set an example for other sectors. Moreover, the government funds, regulates and steers technological development and adoption in many areas, while providing many of the basic programs and infrastructural systems which drive the digital economy (e.g., skilled workforce, broadband in remote areas, business supports, tax credits for digital media and content). But government is not the only actor with a role to play:
- Businesses drive technological innovation to create jobs, increase overall productivity, and provide valuable products and services to the public.
- Civil society brings together local communities, research and academia, public institutions and industry – to develop social consensus on norms, standards and practices which can guide the use of technology. Through collaborative cross-sector initiatives, civil society can create common cause and advance innovative solutions to emerging digital and data challenges.
- Individuals, whether citizens, educators, caregivers or patients, producers or consumers, can become more empowered to take the steps to protect themselves and their families through awareness, knowledge and the right tools.
By promoting the ethical and responsible use of data-driven technologies, we can address public concerns and bolster trust and confidence in their use. Leading organizations and governments have shown that there are many paths to accomplishing this task – but the understanding of underlying issues is still evolving, and there are still few mature models to emulate. A variety of promising tools are being developed – such as data trusts, and algorithmic impact assessments – which balance the need for new safeguards with the opportunities to leverage data for benefit. These can be implemented in a variety of contexts and sectors.
Together, Ontarians can ensure that the benefits of the data revolution are widely shared, while limiting the negative impacts. The following sections highlight leading initiatives which are actively contributing to these shared goals. These sections also begin to describe the aims of Ontario’s Data Strategy in greater detail.
Current Ontario government initiatives
Alongside Ontario’s Data Strategy, the provincial government is pursuing an array of initiatives to modernize public sector data governance, and more broadly to promote trust and confidence in the province’s data economy. These include:
- Minister’s Digital and Data Task Force: In June 2019, the Ministry of Government and Consumer Services established a short-term advisory body comprised of experts on data-driven innovation. The role of the Task Force is to make recommendations on Ontario’s data regime, provide advice to the Minister, and review and provide advice on the government’s implementation efforts. Importantly, the Task Force will participate in the development of Ontario’s Data Strategy, from advising on our discussion papers to engaging in public consultations.
- Privacy Protective Public Sector Data Sharing: Ontario has substantially amended legislation that governs access to the information held by public institutions in Ontario (Freedom of Information and Protection of Privacy Act, or FIPPA). These amendments allow provincial ministries to collect, analyze and more efficiently share data within government to better inform decision-making and the evaluation of programs and services. The province will develop data standards that will set rigorous standards for collecting, linking, de-identifying, retaining and disposing of personal information.
- Digital First: Promoting a Digital First approach for government and the public sector, which includes enshrining digital and data standards in regulation under the Simpler, Faster, Better, Services Act. These standards will promote responsible data management, user-centered privacy and security practices, and the public release of non-sensitive data throughout Ontario’s public sector.
- Broadband Strategy: Many Ontarians across the province still cannot participate in the digital and data-driven economy due to gaps in affordable and high-quality Internet access. Through Ontario’s Broadband and Cellular Action Plan, the province is investing $315 million over five years to expand broadband access in underserved areas, to expand access to reliable, fast and affordable broadband internet connectivity across the provinces.
- Strengthening Privacy Protections in Public Safety: Through the Police Record Checks Reform Act, Ontario is the first province in Canada to legislate standard types of records which can be released through a police record check, supporting public safety while protecting the privacy of Ontarians.
- Data-Driven Anti-Fraud Measures: Working with the Financial Services Regulatory Authority (FRSA) and the Ontario Provincial Police’s Serious Fraud Office (SFO), the government will develop an anti-fraud strategy to combat fraud in auto insurance. This strategy will include using enhanced data analytics to detect fraud, so that taxpayers are not paying for the dishonest actions of fraudsters.
Footnotes
- footnote[1] Back to paragraph Meeting 152 of the House of Commons Standing Committee on Access to Information, Privacy and Ethics. Remarks by Jim Balsillie. 28 May 2019.
- footnote[2] Back to paragraph Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things. EMC Digital Universe and IDC. 2014.
- footnote[3] Back to paragraph Open Data: Unlocking innovation and performance with liquid information. McKinsey Global Institute. 2013.
- footnote[4] Back to paragraph Governing the Future: Creating standards for artificial intelligence and algorithms. The Mowat Centre. 2019.
- footnote[5] Back to paragraph Consumer IoT security gaps have become such a concern that Japan is performing national IoT ‘war games’ to detect weaknesses in national cybersecurity. See also IoT Security for Policymakers. The Internet Society. 2018.; and, Risk or reward: What lurks within your IoT? KPMG. 2018.