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EU to Invest €6 Billion to Build a Single European Data Space
The EU plans to invest €6 billion over the financial period 2021-2027 to build a single European data space, reports EURACTIV. The envisioned space will house personal, business, and “high-quality industrial data” (i.e. IoT/sensor data) and create the infrastructure for data sharing and use across businesses and nations.
The “European Strategy for Data,” published by the European Commission on February 19, aims to overcome the “legal and technical barriers to data sharing across organisations, by combining the necessary tools and infrastructures.” The proposal calls to establish data centers in nine strategic sectors: manufacturing, health, finance, energy, climate, agriculture, mobility, law and public procurement, and skills.
The Commission will also fund the creation of the following:
- A legislative framework to support data sharing
- Federated cloud infrastructures
- Data architectures
- Interoperability requirements and standards within and across sectors
- Data sharing tools
- Governance mechanisms
As a result of this work, data will be available across the EU in machine-readable format, for free.
Creating the legislative framework for data governance is listed as the first priority, followed by adopting an implementing act on high-value data sets in Q1 2021.
Data is the major prerequisite for AI. You need lots and lots of it, of good quality and high variety. Meaning, the more diverse the data used for AI/machine learning, the higher its value and potentially the benefits. Today, most data is held by private corporations, and a lot of it is controlled by Google and Facebook. A typical organization only has access to its own data sets plus some public (or partner) data and whatever is available as open source. It does not have access to, say, competitor information – outside of highly aggregated peer comparisons by third-party benchmarking services – even if both parties were eager to exchange their data sets.
In AI, federated learning has attempted to overcome this limitation by pushing learning to the edge, where an algorithm only has access to the local data on a device (say, a wind turbine for predictive maintenance) within a specific organization. Such local models are then integrated on a periodic basis into a global model, so that all wind turbine manufacturers using this model can benefit from the local learnings on their own devices as well as those of their competitors.
The emerging data marketplaces are another step in this direction. Similar to stock exchanges (or perhaps more like the old commodities exchanges), they aim to facilitate data trading and thus its monetization. (Most organizations use somewhere between 1 and 10% of the data they collect.)
Now, the “European Strategy for Data” promises to remove further obstacles to data integration, at least in Europe. By creating the technical, legal, and ethical infrastructure for data sharing, the EU will promote pan-European data exchange, increase data utility, its use, and ultimately its value, so that many more organizations and the public can reap the benefits from AI – all in a manner that promotes trust and respects fundamental human rights. The framework will also serve as a counterbalance to Google’s and Facebook’s dominance over data.
That is assuming it will be successful. This is a very ambitious, expensive, highly complex endeavour of enormous magnitude that will require close collaboration across all 27 EU members, many business sectors, and numerous organizations within and across the member states. I am reminded of an old joke: if you ask 10 lawyers for their opinions, you’ll get 11 back. This project will face similar challenges. We genuinely hope that it will be successful, though. Where there is a will there is a way, and a few recent EU initiatives to establish ethical safeguards for AI showed that it can move quickly.
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Informatica World 2022 Highlights
On May 24-25, Informatica held its annual conference in Las Vegas – the first time “in-person” since the beginning of the COVID-19 pandemic.
AI Registers: Finally, a Tool to Increase Transparency in AI/ML
Transparency, explainability, and trust are pressing topics in AI/ML today. While much has been written about why these are important and what organizations should do, no tools to help implement these principles have existed – until now.
IBM Raises Price on Software Support; Shoves Customers Toward the Cloud
IBM is changing the terms of its ubiquitous Passport Advantage agreement to remove entitled discounts on over 5,000 on-premises software products, resulting in an immediate price increase for IBM Software & Support (S&S) across its vast customer landscape.
PHEMI: A Data Privacy Tool for Healthcare Providers
PHEMI is a data privacy solution focused on keeping data-processing activities secure by redacting information based on the role of the accessor. Thus, allowing such data to be used for multiple use cases without compromising privacy.
What Is Emotion AI and Why Should You Care?
Recently I attended the inaugural Emotion AI conference, organized by Seth Grimes, a leading analyst and business consultant in the areas of natural language processing, text analytics, sentiment analysis, and their business applications. So, what is emotion AI, why is it relevant, and what do you need to know about it?
Dell Boomi Acquires Unifi: Is That Enough to Cover Its Existing Capability Gap?
Boomi, a Dell Technologies business, has been known for its lack of hierarchy and relationship management capability in its Master Data Hub (MDH) offering. Acquiring Unifi Software does not seem to fill this void but could even cannibalize MDH – unless the two products are merged into one.
Immuta Named to Fast Company’s 2020 List of the World’s 50 Most Innovative Companies
Joining the ranks of giants such as Snap (Snapchat’s parent company), Microsoft and Tesla, Immuta the automated Data Governance company has been named to Fast Company’s 2020 list of the World’s 50 Most Innovative Companies.
Databricks Lakehouse Combines the Best of Data Lake and Data Warehouse in a Single Platform
Databricks has launched a new Data Ingestion Network, made up of partners whose integrations to Data Ingest provide hundreds of connectors and enable automation to move disparate data into Databricks’ new storage layer, eliminating the need to maintain siloed data in a data lake and data warehouse.
TIBCO Acquires Orchestra Networks: Potential Centerpiece of a New Super Smart Data Management Platform
Orchestra Networks was earning attention even before TIBCO’s acquisition. Now that it is part of the TIBCO family of software products, it can become the centerpiece of a very powerful data management, governance, integration, and analytics platform.