10 tips for maximizing data-driven innovation

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There is great social and economic value in big data and data-driven innovation, but mitigating the security and privacy risks associated can push policymakers to curb its use entirely. However, this does not need to be a zero-sum game, according to a new report.

Released May 20, the Software & Information Industry Association’s white paper, “Data Driven Innovation: A guide for policymakers,” details the costs and benefits of data-driven innovation, providing a roadmap for public policy that encourages data-driven innovation while addressing security and privacy concerns.

The paper calls on policymakers to proceed carefully and avoid policies that aim to curtail the use of data “as they could stifle this nascent technological and economic revolution before it can truly take hold.”

Policy recommendations include:

Data-driven innovation requires a policy framework that provides for an evolving view of privacy rights: Policymakers should consider the opportunities and challenges of DDI, while balancing the spectrum of privacy laws and potential privacy risks. They should also recognize socially acceptable norms of privacy are evolving along with technology.

The principle of data minimization should be re-interpreted in light of DDI: Combining technological privacy methods and adhering to responsible data principles can create an effective framework for data minimization, balancing privacy with innovation and accounting appropriately for risk.

Policymakers should encourage de-identification as a way to balance the needs of DDI and privacy protection: Often, when personal information is collected, it can be de-identified in a way that does not affect its value or utility. Public policy should encourage this de-identification where appropriate, but avoid overarching mandates to this end.

Uniform rules should not apply broadly to the collection of personal information and the role of consent: Policymakers should consider the viability of obtaining informed consent and be targeted and specific about which circumstances require explicit consent when collecting personally identifiable information.

Policymakers should promote technology neutrality and avoid technology mandates: For innovation to flourish in the DDI ecosystem, technological neutrality is a must.

Open standards are critical enablers of DDI, but they must continue to evolve through industry-led standards development organizations, not governments: Government can play a key role as a facilitator and convener, applying open standards practices to its own data, and encouraging and facilitating agreement around open standards. Nonetheless, government should avoid enacting policies imposing requirements around specific technical standards or trying to create new standards where none existed prior.

Policies should allow data collectors and controllers to work with data management and analytics suppliers to comply with privacy and security rules through contracts across varying jurisdictions: Government should allow data policy frameworks to interoperate to ensure data management and analytics services can be provided across borders and jurisdictions.

Policies must continue to balance the need of protecting the privacy of students, while enabling DDI to greatly enhance the teaching and learning experience: Students and educational institutions benefit from technology-based educational products and services through cost savings and more efficient teaching methods. Providers of technology-based educational products often use technology to improve their services. Policies should carefully balance the need to adequately protect children’s privacy without undermining the ability of these providers to leverage DDI.

Governments should adopt policies that leverage DDI to make government more efficient and reduce waste: Policies should increase the use of data analytics to make strategic decisions, encourage research and development around data science and encourage training for data scientists and professionals.

Governments should continue to embrace open data policies and public-private partnerships that maximize access to critical public data: Government should encourage open data policies, use public-private partnerships to provide access to critical public data and adopt enterprise architectures that enable sharing. These steps will put public sector data to innovative uses.

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big data, data analytics, Government IT News, Innovation, open data, Tech
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