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Showing posts with label privacy. Show all posts
Showing posts with label privacy. Show all posts

Wednesday, July 8, 2015

The Discriminatory Dark Side Of Big Data


It has happened again. Researchers have discovered that Google’s ad-targeting system is discriminatory. Male web users were more likely to be shown high paying executive ads compared to female visitors. The researchers have published a paper which was presented at the Privacy Enhancing Technologies Symposium in Philadelphia.

I had blogged about the dark side of Big Data almost two years back. Latanya Sweeney, a Harvard professor Googled her own name to find out an ad next to her name for a background check hinting that she was arrested. She dug deeper and concluded that so-called black-identifying names were significantly more likely to be the targets for such ads. She documented this in her paper, Discrimination in Online Ad Delivery. Google then denied AdWords being discriminatory in anyway and Google is denying to be discriminatory now.

I want to believe Google. I don’t think Google believes they are discriminating. And, that’s the discriminatory dark side of Big Data. I have no intention to paint a gloomy picture and blame technology, but I find it scary to observe that technology is changing much faster than the ability of the brightest minds to comprehend the impact of it.

A combination of massively parallel computing and sophisticated algorithms to leverage this parallelism as well as ability of algorithms to learn and adapt without any manual intervention to be more relevant, almost in real-time, are going to cause a lot more of such issues to surface. As a customer you simply don't know whether the products or services that you are offered or not at a certain price is based on any discriminatory practices. To complicate this further, in many cases, even companies don't know whether insights they derive from a vast amount of internal as well as external data are discriminatory or not. This is the dark side of Big Data.

The challenge with Big Data is not Big Data itself but what companies could do with your data combined with any other data without your explicit understanding of how algorithms work. To prevent discriminatory practices, we see employment practices being audited to ensure equal opportunity and admissions to colleges audited to ensure fair admission process, but I don't see how anyone is going to audit these algorithms and data practices.

Disruptive technology always surfaces socioeconomic issues that either didn't exist before or were not obvious and imminent. Some people get worked up because they don't quite understand how technology works. I still remember politicians trying to blame GMail for "reading" emails to show ads. I believe that Big Data is yet another such disruption that is going to cause similar issues and it is disappointing that nothing much has changed in the last two years.

It has taken a while for the Internet companies to figure out how to safeguard our personal data and they are not even there, but their ability to control the way this data could get used is very questionable. Let’s not forget data does not discriminate, people do. We should not shy away from these issues but should collaboratively work hard to highlight and amplify what these issues might be and address them as opposed to blame technology to be evil.

Photo courtesy: Kutrt Bauschardt

Monday, February 11, 2008

Data encryption as a new class of DoS

Not to sure what to make out of this argument. Experts from IBM Internet Security Systems, Juniper, nCipher argue that data encryption is a new class of DoS. The post says "It's a new class of DoS attack.. If you can go in and revoke a key and then demand a ransom, it's a fantastic way of attacking a business." This does not make any sense. If someone can get your private key revoked you would have a lot to worry about other than data encryption.

It also says "Another risk is that over-zealous use of encryption will damage an organization's ability to legitimately share and use critical business data". The storage is encrypted but the access is not, so I am not sure what sharing issues the post is talking about. The leading database vendors such as Oracle provides column level encryption where data is encrypted before it is stored but it is decrypted on-the-fly when accessed and it is very transparent to the user or to the application. Though a limited set of real-time data should be encrypted since there is an overhead of decryption every time the data is accessed and the physical and digital security of the real-time data store is much better than an off-line storage such as backup tapes . On the other hand the backups should always completely be encrypted because they are not supposed to be accessed in real time and there is a greater risk of loosing a tape from a UPS truck or get stolen by baggage handlers. In fact Oracle once considered not to allow taking unencrypted backups at all.

What really matters is the encryption strategy of the organization for the data accessed in real time and the data that gets backed up on a tape. Some simple key management solutions and the right decisions and governance can solve the supposed DoS problems that are being discussed. You could take any tool and use it a wrong way and then complain about the tool itself. Encryption is just a tool and an enabler and you have to figure out how to use it. If you closely look at the "experts" in the post they are into the key management business and want you to believe that your keys will be revoked one day and you might end up paying ransom and also risk your data so why not pay us now and buy our software.

Saturday, February 2, 2008

Monetizing social networks and preserving privacy - an oxymoron?

How do social networks monetize their core platform and applications? It's more than a billion dollar question, figuratively and literally. The social network companies such as Facebook does recognize the potential of an open platform for participation and developer-friendly attitude to let the community sip the champagne of the social network data. There is a plethora of applications built on Facebook platform and and this might be the key towards monetization. The other key players have also been experimenting with their platforms and business models but there is no killer business model, at least not yet.

Monetizing efforts do ruffle some feathers on the way since it is intertwined with other factors such as privacy, data portability, and experience design. The Facebook's experience design keeps applications' users inside of Facebook but at the same time provide the necessary, or sometimes unnecessary, access to user's data to the application providers. This has set off some debates around privacy concerns. Access to user's data and open architecture is a key to increased adoption that can potentially lead to monetization, but Facebook needs to be careful here not to piss of the users. Compare this with Google few years back where Google made a conscious decision to keep the search results rank clean (do no evil) and that strategy paid off when Google started monetizing via AdSense.

Marketers argue that the spending power of the current demographics of Facebook is not high, so why bother? This is true but don't forget that when these millennial grow up to buy that 60" plasma TV, some companies do want to make sure that they have a brand tattooed in their heads from their previous branding experience on such social networks. As pointed out by many studies, the millennial are not brand loyal and that makes it even more difficult for the marketers . The Facebook is a great strategic brand platform to infuse the brand loyalty into these kids.

Data portability is part of longer term vision for any social network. The applications are constrained inside a social network, but an ability to take the data out in a standard format and mesh it up with an application outside of Facebook has plenty of potential. Leading social and professional network providers have joined the Data Portability Group. Imagine to be able to link your Facebook friends with your LinkedIn contacts and provide a value add on top of that. There are plentiful opportunities for the social network providers to build the partner ecosystem and have the partners access to the data and services in the process of co-innovation. LinkedIn for the longest time resisted providing any APIs and relied on their paid subscription services. LinkedIn has tremendous potential in the data that they posses and standardizing the formats and providing the services has many monetization opportunities. It is good to see that LinkedIn has also joined the Data Portability Group and has also promised to open up APIs. Google's OpenSocial effort, partially opening up Orkut as a sandbox, and social network visualization APIs are also the steps in the right direction.

What I can conclude that the growth of such social networks is in two directions, platform and verticals. As platform becomes more open we can anticipate more participation, larger ecosystem, and service innovation. This should help companies monetize (no, no one has figured out how). The growth in vertical will help spur networks for specific verticals such as employment, classifieds, auction - who knows?

Monetization, experience design, and privacy cannot be separated from one another and few wrong strategic decisions could cause significant damage to the social network providers and their users.
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