Some time ago, Stephen Hawking said, “Success in creating effective AI could be the biggest event in the history of our civilization or the worst. We just don’t know. So, we cannot know if we will be infinitely helped by AI, or ignored by it and sidelined, or conceivably destroyed by it.”
Now you may be thinking, “Why is this article beginning with that specific quote from Hawking?” Namely because I believe Hawking hit the nail on the head in essence when he stated that we simply cannot know how big of an event the creation of AI will be for humanity. Herein I will go over my thoughts on its impact on Social Media, but let’s keep in mind that AI today is nothing to what it will be next year, or five years later as the technology is advancing at a blistering pace.
Before we jump in, let me just say that I believe AI brings a lot of positives with it, but there are always unintended negatives and I think it’s important to analyze the impact of those, and properly measure them to understand the true net value of its impact.
AI algorithms enacted into the social media environment have empowered platforms to analyze user data and behavior like never before. The result of this is personalized content to a degree previously thought impossible or unattainable. Being able to directly reach your target audience with pinpoint precision, once a marketer’s dream, is now a daily reality.
Today the user experience for each individual is more tailored to suit them which helps in improving their platform engagement as their satisfaction precipitously grows. With little or no direct effort from the user, the platform learns and auto adjusts itself to the user and serves them better. I ask you, “Who wouldn’t be attracted to this proposition?”
Improved Customer Service
Moving on into improved customer service; through AI, social media platforms can better serve their users. When various platforms collect as much data as these do, it subsequently allows them to service the user, or customer, in ways even the user is more often than not surprised by. Therefore, the platforms can target anticipating customer service needs in a proactive manner.
However, consider that now the customer quickly catches on to the increased service. This can lead to, at times, a more demanding or high maintenance user. This high maintenance user puts more emphasis on the AI learning at a faster rate to quickly anticipate the user’s actions and desires. It creates a cycle which can be a bit vicious at times.
Take for instance chatbots and their ability to render human-like service in most cases. Though as human needs/desires are infinite, a curve ball can always suddenly enter the mix, prompting the system to draw in a human operator to handle the need. Yet AI is learning faster and faster so I imagine it’s only a matter of time before it irons out this minor kink.
Ah content moderation, the hot topic for many an active user nowadays. Everyone has their own opinion on that which should be monitored vs that which can be left alone. Social media does have a tendency to breed a lazy mentality in the user and self-moderating is often forgotten. Regardless, as long as ads are a part of the platforms, some level of AI moderation is needed.
AI can be leveraged by these platforms to root out content that is objectively negative. The algorithms developed have shown a strong ability to quickly identify and flag negative content which in turn helps the platform operators project an appearance of control over their free to use platforms.
AI naturally has an acute ability to analyze all that collected data social media giants have sitting around; more quickly, efficiently and effectively than any human can do. This data can then be put to use immediately in every pro I list herein. One of the keys, as we all inherently understand, to social media is the data it collects and ability to analyze and use said data. AI’s power here is undeniable, enabling businesses which leverage these platforms to create more personalized content and directly reach their target audience.
Finally, I come to the holy grail so to speak, the thing that everyone enjoys, automation. Honestly, anytime something can be automated, it’s hard to argue against automating that thing. Of course, there are always exceptions, but in the case of social media let’s consider the new possibilities thanks to AI.
Businesses can now streamline content marketing activities improving work efficiency and general productivity if implemented correctly. AI powered-tools help free up social media managers time to focus on more important tasks that require their attention. For example, AI ad-campaign management tools can auto adjust for bids, creativity, target market and so on based on the performance data coming in; linking to the data analysis power of AI in my previous point.
Nothing is without its drawbacks; I will begin the cons with a big one: bias. The algorithms learn what users like and want to see which is great for creating a tailored experience, but not so great in that it insulates the user to that which only confirms what they believe. Consider that if the data the algorithms are analyzing or even the algorithm itself is biased, content shown to the user will take that specific angle.
Perhaps we should acknowledge that for everything good, there is always a bad element that can be exploited, whether or not advertently or inadvertently. Therefore, more onus is put on social media operators to develop and train AI algorithms responsibly.
Loss of Certain Jobs
The fear of a machine taking one’s job has been in the human psyche for as long as we have been living with and developing technology. Today that fear is much more prevalent as AI becomes more and more capable. The question we must ask is, “What jobs are at risk and is protection genuinely necessary?”
When the combine harvester was created, though the majority of people at the time saw their jobs vanish, few complained as farming is not something most people want to do. However, if AI begins to take over more previously “human only” tasks, there will be push back and it appears that for the foreseeable future the pushback will only grow before eventually subsiding. Automating taxis and buses is one thing, but automating content design or creation is a whole other thing.
Shift in Human Experience
Now for the human experience aspect of AI’s impact on social media. There is no denying the earth-shattering effect social media has had on our lives. Many may feel or even believe having AI take over managing many aspects of social media for us will create a paradise of sorts, reducing the amount of time they need to dedicate to their interaction and work with social media. However, that which becomes more efficient must also become equally more productive which puts strain on our experience in the workplace.
This will push people to their limits to ensure their value in the job positions they have while simultaneously acknowledging that in failing to do so, their job may become forfeit to AI rather through redundancy or direct automation of the tasks they are handling.
AI boosts content creation for social media platforms at a rate that humans cannot keep up with. There are ethical concerns therein related to the nature of the content AI creates and the data it leverages to do so. What we typically relied on a human to use the judgment and knowledge of our unique experience, now is done by an unemotional machine for better or worse. What a human may judge as private, AI may see simply as content to post without considering any of the ramifications that may occur. AI is not concerned with your data protection, only with using your data to fulfill its mission.
I have mentioned this briefly in some of my points above, but I want to bring attention directly to it. Algorithms can be exploited are great, but like anything we create, they can be exploited for both good and bad purposes. Bad actors online can use algorithms to engage in nefarious activities that are harmful to the communities within social media platforms. With AI, bots have become a headache that businesses now have to dedicate more resources to dealing with which eats into the value that social media and AI offer.
Lack of Transparency
Finally, AI leads to a lack of transparency as the algorithms are often unbelievably complex and demanding to comprehend. Users begin to wonder why certain decisions are made and how those decisions were made; only to later discover it was AI that levied the decision and strongly reject it on the basis of the lack of human input. There will always be dissent to a decision, but when made by AI, we find that the dissent grows as the lack of transparency in the decision process is blindly obvious to all.
I’d like to wrap up by saying, I’m neither against nor for AI in social media. Naturally I believe the technology has the potential to do some great things in space but also acknowledge there are many unknowns and careful consideration is needed before charging forward. In order to realize the benefits and minimize the risks, businesses must demand transparency from the platform operators. That, along with a priority put on privacy and open source access for all to the AI tools. Ultimately, the impact of AI on social media will depend on how it is used and regulated in the years to come… time will tell!
Tag CloudAgile - Agile Delivery - AI - amazonecommerce - Animal Framework - Attracting talent - Autonomous weapons - B2B - blockchain - businessbuilding - Business building - Clean code - Client consulting - cloud platform - Code Refactoring - coding - Company building - Computer Vision - Corporate startup - cryptocurrencies - de-risking business building - Deepfakes - Deep Learning - DeepMind - derisking business building - Design Research - Developer Path - DevOps - Digital Ownership - Digital Product Strategy - ecommerce - entrepreneurs - Figma - founder equality - founder equity - front end developer - Fullstack Engineer - Growth strategy - Hook model - Incubator - innovation - Iterative and Incremental Development - legacy system - Manual Testing - Metaverse - methodology - Mobile Engineer - Natural Language Processing - NFT - NLP - online recruitment - playbooks - Podcast - Product Design - Product Development - Product Development Strategy - Product strategy - product versions - project management - Prototyping early-stage ideas - Quantum Computing - Recruitments - Remote Work - Research - research problem - Robotics - Sales machine - scalable software - Scrum - Self-Driving Cars - Serial entrepreneurs - Slash - software - software design - Software Development - Software Development Company - Software Engineering - Spotify Model - Staff Augmentation - teamwork - Tech Talks - tech teams - tech vendor - testing playbook - The Phoenix Project - Unit testing - user interview - user retention design - VB Map podcast - Venture Building - Venture building strategies - Venture Capital - venturecapital - virtual retreat - Web3