Trust and safety (T&S) is important in creating a secure and reliable environment for users engaging in online platforms, services, and transactions. It incorporates different elements, such as protecting users from scams and harassment, moderating content by providing practical guidelines on what is acceptable, and encouraging fairness and transparency for a positive user experience.
As online platforms grow to accept more users, it is becoming more evident that robust policies and measures are needed to promote online safety. AI promises to ensure organizations can keep up with their users and provide a safe and conducive environment. However, can AI be fully trusted to achieve this important task?
This article will explore the role of AI in ensuring online safety and discuss the challenges of using AI as a trust and safety tool.
Key Takeaways
- Artificial intelligence plays an important role in ensuring online safety for all users.
- Some of AI's main benefits include uncovering hidden threats, scaling efficiently, and adapting to evolving threats.
- However, AI also faces challenges that might make it unsuitable for profiting from trust and safety in online environments.
- Issues such as biased data and malicious manipulation can hinder its effectiveness in promoting safety for online users.
- Ultimately, the best approach to AI as a trust and safety tool is to treat it as a human companion rather than a replacement.
The Promise of AI for Online Safety
On any given day, vast amounts of data flow through online platforms. This presents a significant challenge for maintaining a safe and secure environment. Artificial intelligence can help boost and sustain online safety through:
Unveiling Hidden Threats
AI can analyze massive data sets of text, images, and videos relatively quickly. This allows it to identify harmful content like hate speech, violent threats, and illegal activity faster and more accurately than human moderators. For example, AI can analyze millions of posts and detect subtle signs of cyberbullying that might escape human attention.
Scaling Efficiently
Human moderators face limitations in handling the ever-growing volume of online content. For example, cybercriminals are increasing the amount of spam they share daily. Identifying and stopping all the instances of spam can prove hectic and unrealistic for human moderators.
On the other hand, an AI system trained to identify spam can analyze countless messages simultaneously, freeing human moderators to focus on complex or borderline cases.
Adaptability
Threats and abuse are not always as straightforward as most people imagine. Sometimes, they are hidden in nuance and other forms of communication, such as emojis and GIFs.
Other times, communication evolves as technology expands, thus providing malicious actors with more avenues to hurt people online. Training AI to detect such threats and different forms of abuse that might evolve is possible.
Proactive Protection
AI can analyze user behavior patterns to identify potential risks before they escalate. For example, imagine a user on a particular online platform suddenly exhibiting aggressive behavior through their posts and comments. A properly trained AI system can flag the account as the behavior escalates, allowing human moderators to intervene in time.
The Challenges of Trusting AI
While AI is an exciting and helpful tool, it does have its share of challenges that might affect its use in ensuring trust and safety for people interacting online.
Some of these challenges include:
Biased Data, Biased Outcome
AI algorithms rely on data input and are only as good as the data they are trained on. Imagine a particular AI algorithm used to help a financial institution approve loans. If the data used to train the AI contains racial bias, for example, the AI might struggle to assess the demographic against which the data discriminates objectively.
Lost in Translation
Translating human communication can be a complex activity. Human communication is rich in context and nuance.
For example, a simple statement like “you dog” could mean different things based on the context of a conversation. An AI system used in content moderation can’t read these contexts and might end up flagging such speech as hate speech or insults. In addition, things like sarcasm, humor, and cultural references might escape AI systems that do not understand the underlying intent.
Malicious Manipulation
Another challenge AI faces in ensuring trust and safety in online human interactions is malicious manipulation. This involves intentionally feeding the AI with biased or harmful data. The data might be aimed at discriminating against a particular demographic, rendering the AI useless in providing fair moderation in online interactions.
This manipulation of the data can happen at any level. It is, therefore, important to implement and adhere to robust security measures to protect AI systems from manipulation.
Finding the Balance: AI as a Tool within a Human-Centered Approach
Is it enough to see the challenges affecting AI and dismiss it summarily, or should we focus on the benefits and adopt it as a trust and safety tool?
A better approach to AI as a trust and safety tool is to treat it as a human companion rather than a replacement. This human-centric approach will help you maximize the benefits and minimize the drawbacks of using AI.
Here is why a human-centered approach is essential:
It will reduce Human-AI Conflict
Human-AI conflict in this context involves situations where AI and humans cannot agree on whether a piece of content is harmful. For example, imagine a situation with cultural nuances—an AI might miss a joke while a human moderator can understand its true meaning.
While the AI can flag suspicious activity online, only experienced human moderators can assess context, weigh intent, and make informed decisions, especially in borderline cases.
There will be more Oversight and Accountability
Sometimes, AI can make opaque decisions, such as flagging and even removing particular content without explaining. Human moderators can review AI decisions, identify potential errors or biases, and ensure alignment with community guidelines in such situations. This helps maintain trust and transparency in the content moderation process.
It Diversifies Training Data
One of the most important aspects of AI is the data it is trained on. Remember, an AI system is as good as the data it was trained on. This includes regular monitoring of AI performance for bias. Adopting a more human-centric approach introduces diverse datasets that reflect the real world. This helps AI systems make fairer and more inclusive decisions.
The Best AI Solutions for Trust and Safety
Providing a conducive environment for online interactions is one of the important pillars of running successful platforms. While most solutions work, they usually come pre-built with fixed detection policies that might not fit every company. They are usually less flexible and cannot typically interpret context and make nuanced decisions, potentially leading to unfair content moderation.
AI solutions, such as Intrinsic, provide a friendlier solution. It is a fully customizable AI content moderation platform meant to mimic human moderators, allowing moderation to take a more human-centered approach.
Some of the benefits you can expect from Intrinsic include:
- Explainable AI – This makes it easier for human moderators to understand why the AI flagged certain content, building trust in the system. It helps identify areas where the AI might be making mistakes, refine the moderation process, and enables users to challenge moderation decisions by providing insights into the reasoning behind them.
- Real-time Detection—This aids in a faster response to harmful content such as hate speech and harassment, allowing for quicker intervention. It also helps prevent the spread of negativity by catching issues before they escalate, thus creating a safer environment for users by minimizing exposure to harmful content.
- Automated Moderation—This allows scalability by efficiently handling large volumes of content, freeing up human moderators for complex cases. It also enforces community guidelines uniformly, reducing bias and ensuring fairness. Finally, it helps maintain constant moderation, regardless of time zone or human availability.
By modernizing trust and safety, Intrinsic allows users to stay ahead of evolving abuse and compliance risks that might make platforms difficult to use.
Conclusion
So, Can AI be trusted to ensure online safety?
The long and short answer is yes.
Maintaining trust and safety requires innovative solutions to keep up with the ever-evolving online landscape. AI presents a powerful solution with its ability to analyze vast amounts of data and identify harmful content at scale. However, despite its abilities, AI does have limitations that might make online platforms unfriendly for handling diverse groups of people.
This makes it crucial to have a human-centered approach when working with AI. Experienced human moderators can work alongside AI to provide a more balanced approach towards trust and safety, thus making online platforms safe for all.
Top comments (0)