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The Biggest Risks of Artificial Intelligence + How to Combat Them

The Biggest Risks of Artificial Intelligence + How to Combat Them

Like any new technology, AI brings some risks to the table. Here’s how to combat those concerns and take full advantage of AI’s benefits.

Written by:
Luke Daugherty
September 5, 2024
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Go online, browse social media, or turn on your TV, and you’re bound to find something about artificial intelligence (AI) these days. AI has been front and center in advertising in recent years, making it clear that corporations are all in on this technology.

As eager as big tech is to embrace AI, however, the general public has mixed feelings about the sudden AI trend. Many people can’t shake the fear that AI is dangerous, a threat to jobs or humanity itself.

While it’s important to take these concerns seriously, it’s also crucial to keep them in context. It’s normal to feel anxious or uncertain about any big technological change, and caution is warranted with one as momentous as this. The best way to address the risks of artificial intelligence is to tackle them head-on, speaking openly and frankly about how to put proper guardrails in place. With that in mind, here are some of the biggest potential harms of artificial intelligence — and how to combat them.

1. Lack of Transparency

Transparency is at the heart of all worries about the threats of AI. When technology has a mind of its own (at least to some degree), the lines of accountability and responsibility get fuzzy. Where does AI get its information? How do we know it’s reliable? What protections are in place to prevent misinformation or abuse? These questions — and more — are crucial for building a safe foundation for using AI technology.

The impetus is, of course, on companies creating AI models to be open about the algorithms behind their tools and the data used to train them. And they should participate in public dialog and support initiatives to implement appropriate security measures.

Ultimately, though, the impetus is on all citizens to push for adequate AI legislation to ensure tech companies put human interests before profits. The European AI Act is a good example of how the law can address these concerns, and some states are even following suit, such as California’s proposed AI regulations.

2. Data Privacy

Among the many AI security concerns in public conversation in recent years, perhaps none has been more prominent than data privacy. AI tools acquire and process vast amounts of data by scraping the internet and other databases, and this has already raised some important privacy concerns.

Facebook’s Cambridge Analytica scandal is perhaps the earliest example of these potential problems, as the company used AI to mine vast swaths of user data to target political ads during the 2016 election. More recently, concerns have arisen about using personal photos to train facial recognition software.

Legislators are in a position to address these artificial intelligence dangers, but companies using AI technology can take proactive steps to ensure customer data is handled responsibly. Rev, for instance, maintains strict standards for data encryption and how employees interact with any personal information. These types of cybersecurity policies are especially important in fields that deal with highly sensitive customer data, like the legal industry.

Across the board, companies should mandate customer consent before using any personal data with AI tools. Customers should always know how their data is being stored and used — and have the opportunity to opt-out.

3. AI Bias

Although AI can “think” and function somewhat independently, it’s ultimately shaped by its creators — humans. And that means human biases and stereotypes are often reflected or even amplified in AI tools.

There have certainly been newsworthy examples of bias in AI technology — from hiring inequities in employment screening tools to higher error rates for racial minorities with facial recognition software. These biases are often unintentional, based merely on the data used to train the system.

Nonetheless, avoiding AI bias requires a deliberate focus on providing unbiased data sets and creating impartial algorithms. Numerous studies have been done in this arena, and more are in progress to help developers better address bias issues.

4. Physical, Social, and Emotional Harm

One of the biggest perceived AI risks is its potential to do direct harm. AI-powered self-driving cars, for example, have been involved in some fatal crashes — though studies have shown autonomous vehicles are actually safer than those controlled by human drivers.

Besides physical harm, many people worry about the ill effects on society as a whole. The AI-driven spread of fake news has been well documented, and deepfakes have already been weaponized for political gain. Some chatbots have even seemed to encourage users to commit suicide when prompted.

These potential negative effects of AI are serious and not to be downplayed. Tech companies and legislators must work together to set up proper safety protocols before new technology is rolled out. Users, meanwhile, should also take steps to use AI tools safely by thinking critically and protecting personal information.

It’s also crucial to counteract these fears by considering the many potential benefits AI brings to the table. Gains in productivity, more equitable information access, and deeper analytics capabilities can all bring real advantages to individuals and society — as long as the technology is leveraged responsibly and carefully.

5. Loss of Jobs

Job insecurity in the face of new technology is nothing new. But, unlike previous technologies, AI poses a unique threat to jobs that were historically safe from automation.

According to the Pew Research Center, roughly a fifth of American workers have jobs at a high risk of automation by AI. Highly educated workers are twice as likely to be at higher risk. However, the same study finds that workers are more hopeful about how AI can make their work easier or more effective than they are concerned it will take away their jobs.

Going forward, the focus for employers, workers, and the labor market at large should be on helping the workforce adapt to the new technology and incorporate it into their daily routines. (We’ll touch on that more below.)

Combatting AI Fears

So, is AI dangerous? Like any new technology, it has its risks. However, the real question is how we react to big technology changes. Fear only leads to reactivity — and ultimately leaves us more vulnerable.

A healthier approach is to take the risks of artificial intelligence seriously, and then respond proactively to address those worries while making the most of these new tools. For instance:

  • Legislators should follow the example of the EU and craft laws that protect citizens from AI abuses.
  • Corporations can invest in upskilling their workforces and training them to incorporate AI tools into their jobs.
  • Companies must put transparency first, seeking consent for using customer data and providing insights about the algorithms and data behind their machine learning models.
  • Developers must proactively root out biases in data sets and ensure more objective training for AI tools.
  • Systems must be in place to easily validate AI outputs and confirm accuracy.
  • Ethical concerns should be central to all conversations involving key stakeholders in this fast-changing technology.
  • Individuals must advocate for AI protections and ethical guidelines to ensure proper protections are in place.

By being proactive rather than reactive, we can ease many of the fears about AI and keep this technology where it was meant to be — serving the needs of humanity.

Bringing AI Into Your Workflow

There are plenty of examples of companies leveraging the benefits of AI. Marketers, journalists, teachers, and creators of all kinds are using AI to make their work more productive.

Even in a field as meticulous as law, court reports use AI-powered tools like Rev to transcribe depositions and proceedings and do their jobs more efficiently. Plus, Rev’s new VoiceHub productivity platform enables users to quickly and easily pull quotes or create meeting summaries and key points.

Consider the following ways to start integrating AI into your daily workflow:

  • Look for bottlenecks or pain points in the day-to-day. What could be done more efficiently with the help of smart automation? Transcription is a great example of a time-consuming task that can be automated without sacrificing accuracy.
  • Consider your customers. If you work in a customer-facing industry, where is the customer experience falling short? Would a chatbot solution help bridge the gap by improving wait times and helping customers conduct self-service more easily?
  • Address creative blockages. Generative AI tools like ChatGPT don’t need to supplant human creativity. How can you use these to generate ideas or find new approaches to a problem?
  • Compare your options. There are so many AI tools on the market now, it’s important to compare features, data sources, and AI privacy policies to ensure you choose the more effective, safe solution for your needs.

In truth, the possibilities are endless. With proper regulations in place, AI unlocks a world of human potential.

Try AI Technology With a Human Touch

Working with a new technology is always a little disorienting — even unnerving. But AI doesn’t have to be scary. These tools are at their best when working in tandem with people to make human jobs easier.

That’s the power of Rev’s transcription and captioning technology, which uniquely relies on the delicate interplay between AI and humans to create the most accurate, efficient transcripts on the market. Try it for yourself.

Create AI captions today

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