The latest data sharing proposal comes from Prof. Myer-Schonberger, whose previous work on big data and the right to delete information won him a wide following in policy circles. The key idea is that companies above a certain size would be required to disgorge subsets of their data to competitors. Amazon, for example, would provide the world with its sales data so that anyone could create an alternative recommendation engine.\nVoluntary data sharing arrangements among competitors have existed for generations. The most prominent example in the U.S. is credit bureaus, where banks and others voluntarily pool information in order to get a more accurate picture of risks for potential lenders, insurers and employers.\nBut in its proposed universal and mandatory form, data sharing suffers from many flaws, not just detailed implementation difficulties that could be expected to arise with even promising new ideas, but fundamental defects that make it unattractive in principle and unworkable in practice.\nData sharing is a privacy nightmare\nIf people are willing to share their information with Google or Facebook, it doesn\u2019t follow that they want to share it with all the competitors of these companies. Forced data sharing runs against any notion of effective privacy protection. Companies with attractive and desirable data management practices would be required to pass personal information on to other companies with no established consumer protection processes.\u00a0\nThis could all be fixed if companies were required to deidentify the information before passing it on. But of course, identified information is the point. New social networks don\u2019t want anonymous data; they want the list of Facebook\u2019s users and everything Facebook knows about them. Google\u2019s competitors don\u2019t want random search data; they want individual level data, identified by IP address, device ID and other identifiers that privacy regulators treat as personal information. Amazon competitors don\u2019t want aggregated sales data; they want Amazon\u2019s individual level profiles to train their recommendation engines.\nData sharing would also create overwhelming disincentives to invest in data base construction\nThe non-rivalrous nature of information often gives rise to the feeling that there is no loss and all gain from data sharing. Let\u2019s all use it together because it cannot be used up!\nBut free to use does not mean free to produce. Information does not reside in a Platonic heaven.\u00a0 It exists embodied in tangible computer records. The construction and maintenance of accurate, up to date relevant systems of records is an enormously expensive tasks characterized by steep economies of scale. These data bases are often a treasured company asset, with values at transfer in the billions of dollars. It is hard to see why any company would invest in this effort if the fruit of its work would be immediately made available to all competitors at no or minimal charge.\nThe data sharing idea would override private contracts and the European data base directive that provide investors with incentives to create and maintain valuable data bases.\nThe alleged dangers of \u201ccentralization\u201d and \u201ccentral planning\u201d are illusory.\nOf course, antitrust law does not demand that companies with large market shares must be subject to special requirements such as IP or data sharing until other companies are more successful.\nStill, data sharing might be a conceivable response if new companies could not gain access to the information they need to compete fully against incumbents. Yet every time regulators have looked at this issue in merger contexts they have determined that there is enough data post-merger to allow full and effective competition from alternative providers.\nMyer-Schonberger thinks data sharing is needed to ward off system failures that could arise from centralization. When one company provides the best recommendation engine that most people want to use, what happens when the service makes a mistake? There\u2019s nowhere to go to get an alternative answer that could correct the mistake. The result could be catastrophically misleading search results, consumer recommendations, and news feeds. When one company controls all the data, what happens if there\u2019s a security breach? It\u2019s a single point of failure that could have catastrophic results for the entire system.\nBut upon examination these ideas are mostly scary rhetoric. Forced data sharing doesn\u2019t make the data vanish from the original data collector. So whatever security risks were present are still there. And with data sharing, every new entity who receives the original data is a new point of failure.\nIf a company gets its personalized results wrong, consumers don\u2019t need to go to a competitor to be informed of the mistake. It\u2019s like getting the wrong sized shoe; you know it doesn\u2019t fit because it hurts. So, what happens with personalization mistakes? You don\u2019t read the suggested article, you don\u2019t buy the recommended product and you don\u2019t click on the proffered search results. And the algorithm learns from that and tries to get it better next time.\nIf it doesn\u2019t, then there are alternatives. Perhaps the biggest blind spot in the centralization argument is the idea that Amazon doesn\u2019t have competitors like Wal-Mart, Facebook doesn\u2019t have competitors like Snapchat, Twitter and LinkedIn, and Google doesn\u2019t have competitors like Bing and DuckDuckGo, not to mention Yelp and Travelocity. Systematic, regular and widespread failure of these services would not be catastrophic except for the companies themselves, who would immediately see their market share eroded as people exit in mass to these alternatives.\nReformers should look elsewhere for practical remedies\nThere\u2019s a widespread feeling that something is amiss in tech and many policy analysts are in search of remedies that will improve the status quo. In my view, mandated data sharing is an idea in search of a problem to solve. But even those who think the current tech marketplace needs a good dose of reform would be well advised to look elsewhere for practical, workable alternatives.