Uncover The Dangers of Targeted Ads and How You Can Escape Them

2022-09-05
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Have you ever been innocently browsing the web, only to find that the ads shown to you line up a little too perfectly with the conversation you just finished before you picked up your phone? Maybe you've noticed that a title you've seen a dozen times in your recommendations on Netflix looks different all of a sudden, and the thumbnail entices you to give the trailer a watch when maybe it didn't before.

That's because Netflix, and most other companies today, use massive amounts of real-time data — like the shows and movies you click on — to decide what to display on your screen. This level of "personalization" is supposed to make life more convenient for us, but in a world where monetization comes first, these tactics are standing in the way of our free choice.

Now more than ever, it's imperative that we ask questions about how our data is used to curate the content we're shown and, ultimately, form our opinions. But how do you get around the so-called personalized, monetized, big-data-driven results everywhere you look? It starts with a better understanding of what's going on behind the scenes.

How companies use our data to curate content

It's widely known that companies use data about what we search, do and buy online to "curate" the content they think we'll be most likely to click on. The problem is that this curation method is based entirely on the goal of monetization, which in turn silently limits your freedom of choice and the ability to seek out new information.

Take, for example, how ad networks decide what to show you. Advertisers pay per impression, but they spend even more when a user actually clicks, which is why ad networks want to deliver content with which you're most likely to interact. Using big data built around your browsing habits, most of the ads shown to you will feature brands and products you've viewed in the past. This reinforces preferences without necessarily allowing you to explore new options.

Based on how you interact with the ads shown to you, they'll be optimized for sales even further by presenting you with more of what you click on and less of what you don't. All the while, you're living in an advertising bubble that can impact product recommendations, local listings for restaurants, services and even the articles shown in your newsfeed.

In other words, by simply showing you more of the same, companies are maximizing their profits while actively standing in the way of your ability to uncover new information — and that's a very harmful thing.

Related: How Companies Are Using Big Data to Boost Sales, and How You Can Do the Same

What we're shown online shapes our opinions

Social media platforms are one of the most powerful examples of how big data can prove harmful when not properly monitored and controlled.

Suddenly, it becomes apparent that curated content almost forces us into siloes. When dealing with products and services, it might prove inconvenient, but when faced with news and political topics, many consumers find themselves in a dangerous feedback loop without even realizing it.

Once a social media platform has you pegged with specific demographics, you'll begin to see more content that supports the opinions you've seen before and aligns with the views you appear to hold. As a result, you can end up surrounded by information that seemingly confirms your beliefs and perpetuates stereotypes, even if it isn't the whole truth.

It's becoming harder and harder to find information that hasn't been "handpicked" in some way to match what the algorithms think you want to see. That's precisely why leaders are beginning to recognize the dangers of the big data monopoly.

Related: Google Plans to Stop Targeting Ads Based on Your Browsing History

How do we safely monitor and control this monopoly of data?

Data sharing is not inherently bad, but it is crucial that we begin to think more carefully about how our data is used to shape the opinions and information we find online. Beyond that, we also need to make an effort to escape our information bubbles and purposefully seek out different and alternative points of view.

If you go back generations, people read newspapers and magazines and even picked up an encyclopedia every once in a while. They also tuned in to the local news and listened to the radio. At the end of the day, they had heard different points of view from different people, each with their own sources. And to some degree, there was more respect for those alternate points of view.

Today, we simply don't check as many sources before we form opinions. Despite questionable curation practices, some of the burdens still fall onto us as individuals to be inquisitive. That goes for news, political topics and any search where your data is monetized to control the results you see, be it for products, establishments, services or even charities.

Related: Does Customer Data Privacy Actually Matter? It Should.

It's time to take back ownership of our preferences

You probably don't have a shelf of encyclopedias lying around that can present mostly neutral, factual information on any given topic. However, you do have the opportunity to spend some time seeking out contrasting opinions and alternative recommendations so that you can begin to break free from the content curation bubble.

It's not a matter of being against data sharing but recognizing that data sharing has its downsides. If you've come to solely rely on the recommendations and opinions that the algorithms are generating for you, it's time to start asking more questions and spending more time reflecting on why you're seeing the brands, ads and content coming across your feed. It might just be time to branch out to something new.

参考译文
揭示定向广告的危险以及如何避开它们
你是否曾经在上网时无意中发现,刚放下手机不久,广告就精准地与你刚刚的对话内容完美契合?也许你注意到了,Netflix上某个你看了十几遍的标题,突然呈现出不同的样子,缩略图开始吸引你去观看预告片,而以前它也许并不能引起你的兴趣。这是因为Netflix和如今大多数公司都使用大量实时数据——比如你点击的剧集和电影——来决定向你展示什么内容。这种“个性化”本来是为了让我们的生活更加便捷,但在一个以盈利为先的世界里,这些手段正在阻碍我们做出自由选择。如今比以往任何时候都更重要的是,我们要问一问我们的数据是如何被用来筛选我们看到的内容,并最终塑造我们观点的。但你该如何摆脱那些无处不在的所谓“个性化”、“商业化”和“大数据驱动”的结果?这一切都始于我们更好地了解幕后发生了什么。### 公司是如何利用我们的数据来筛选内容的众所周知,公司会利用有关我们在线搜索、行为和购买的数据来“筛选”他们认为我们最有可能点击的内容。问题是,这种筛选方式完全基于盈利目标,这反过来又在默默限制着你的选择自由和获取新信息的能力。举个例子,来看看广告网络是如何决定向你展示什么内容的。广告商按展示付费,但当用户实际点击广告时,他们支付的费用更高,这就是为什么广告网络希望推送你最有可能互动的内容。通过基于你浏览习惯的大数据,大多数展示给你的广告都会是你过去查看过的品牌和产品。这强化了你的偏好,却未必允许你去探索新的选择。根据你与广告的互动情况,它们会进一步优化销售表现,向你展示更多你点击过的内容,而减少你没点过的。与此同时,你正生活在一个广告气泡中,这可能会影响产品推荐、本地餐馆、服务甚至是你在社交动态中看到的文章。换句话说,公司通过简单地向你重复展示相似内容来最大化利润,同时积极阻碍你发现新信息的能力,而这是一件非常有害的事情。相关阅读:公司如何利用大数据提升销售,你也可以这么做。### 我们在线上看到的内容塑造了我们的观点社交媒体平台是大数据在缺乏适当监管和控制时可能造成危害的一个最有力的例子。突然之间,你会发现,这些精心筛选的内容几乎迫使我们进入封闭的信息圈。当你面对的是商品和服务时,这可能会带来不便,但当你面对新闻和政治话题时,许多消费者甚至在没有意识到的情况下,陷入了危险的信息回环。一旦社交媒体平台将你归类到特定的群体中,你开始看到更多内容,这些内容支持你之前的观点,并与你所表现的立场一致。结果是你可能被包围在似乎确认你信念和强化刻板印象的信息中,即使这并非全部真相。我们越来越难找到那些没有经过“人为筛选”的信息,这些信息并非算法认为你想看到的内容。这正是为什么越来越多的领袖开始意识到大数据垄断的危险。相关阅读:谷歌计划停止根据你的浏览历史来投放广告。### 我们该如何安全地监管并控制数据垄断?数据共享本身并不坏,但我们必须更仔细地思考我们的数据如何被用来塑造我们在网上找到的观点和信息。更重要的是,我们还需要努力跳出信息泡沫,主动寻求不同的、替代性的观点。如果你回到几十年前,人们会阅读报纸、杂志,偶尔还会查阅百科全书。他们也会收听本地新闻和广播。最终,他们从不同的人那里听到不同的观点,每个人都有自己的消息来源。在一定程度上,他们更尊重这些不同的观点。如今,我们形成观点时往往不会查阅那么多来源。尽管存在可疑的筛选机制,但我们作为个体仍然肩负着一些责任,那就是保持好奇。这不仅适用于新闻和政治话题,也适用于所有搜索,无论你的数据被用来控制你所看到的产品、商家、服务,甚至是慈善组织的结果。相关阅读:客户数据隐私真的重要吗?它应该重要。### 是时候重新掌握我们自己的偏好了你可能已经没有一整排百科全书可以提供相对中立、客观的信息来了解任何话题。然而,你仍然有机会花些时间去寻找对立的观点和替代性的推荐,从而开始挣脱内容筛选的气泡。这不是反对数据共享,而是认识到数据共享确实有其弊端。如果你已经完全依赖算法为你生成的推荐和观点,那么是时候开始提出更多问题,花更多时间思考,为什么你看到了那些品牌、广告和内容出现在你的信息流中。也许,现在正是时候尝试一些新的东西了。
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