A couple years ago, artificial intelligence still seemed like a somewhat far-off, sci-fi version of reality. And it certainly didn’t seem like something that would completely transform how marketers work within the next few years.
But in 2023, generative AI is officially here, and it’s only growing. In fact, the generative AI market size accounted for over 7 billion USD in 2021, and it’s projected to occupy more than 110 billion USD by 2023 — growing at a CAGR of 34.3%.
All of which is to say: Generative AI is poised to completely disrupt — and elevate — business’ content strategies in 2023 and beyond.
And disruption of any kind can be scary. What does generative AI mean for the future of marketing? Will it replace us, or elevate us? And what about SEO? Will Googling be replaced with AI chatbots — and what does all that mean for content creation? Read More
Tag Archives: Augmented Intelligence
Superhuman: What can AI do in 30 minutes?
The thing that we have to come to grips with in a world of ubiquitous, powerful AI tools is how much it can do for us. The multiplier on human effort is unprecedented, and potentially disruptive. But this fact can often feel abstract.
So I decided to run an experiment. I gave myself 30 minutes, and tried to accomplish as much as I could during that time on a single business project. At the end of 30 minutes I would stop. The project: to market the launch a new educational game. AI would do all the work, I would just offer directions.
And what it accomplished was superhuman. I will go through the details in a moment, but, in 30 minutes it: did market research, created a positioning document, wrote an email campaign, created a website, created a logo and “hero shot” graphic, made a social media campaign for multiple platforms, and scripted and created a video. In 30 minutes. Read More
How will Language Modelers like ChatGPT Affect Occupations and Industries?
Recent dramatic increases in AI language modeling capabilities has led to many questions about the effect of these technologies on the economy. In this paper we present a methodology to systematically assess the extent to which occupations, industries and geographies are exposed to advances in AI language modeling capabilities. We find that the top occupations exposed to language modeling include telemarketers and a variety of post-secondary teachers such as English language and literature, foreign language and literature, and history teachers. We find the top industries exposed to advances in language modeling are legal services and securities, commodities, and investments. Read More
AI is Useful for Capitalists but Probably Terrible for Anyone Else
AI is finally useful for business, and everyone is likely underestimating its impact. But unless AI is open-source and truly owned by the end users the future for everyone but the software providers looks grim.
The last time your author opined about the state of artificial intelligence I predicted that commercial success required two things: first, that AI researchers focus on solving a specific business problem, and second, that enough data exists for that specific business problem. The premise for this prediction was that researchers needed to develop an intuition of the business process involved so they could encode that intuition into their models. In other words, that a general-purpose solution would not crack every business problem. This might have been true temporarily, but it’s doomed to be wrong more permanently. I missed a reoccurring pattern in the history of AI: that eventually enough computational power wins. In the same way chess-playing engines that tried to encode heuristics about the game eventually lost to models that had enough computational power, these AI models for “specific business problems” have all just lost to the hundred billion parameters of GPT-3.
I am not known for being overly bullish on technology, but I struggle to think of everyday sorts of business examples where such a large language model would not do well. It is true that in the above example the model did terribly on questions requiring basic arithmetic (converting rent per square foot per month to rent per square metre per year, for example), but these limitations are missing the point. Computers are known to be adequate arithmetic-performing machines (hence the name), and surely future models would correct this and other deficiencies. Artificial intelligence is now generally useful for business, and I am probably not thinking broadly enough about where it will end up.
One decent guess, however, might be augmented intelligence – the idea that AI is best deployed as a tool to increase the power and productivity of human operators rather than replace them. Read More
Algorithms Will Make Critical Talent Decisions in the Next Recession—Here’s How To Ensure They’re the Right Ones
Nearly all HR leaders say their department will use software and algorithms to reduce labor costs in a 2023 recession, but only half are completely confident their tech will produce unbiased recommendations.
Entering 2023, the dreaded “R” word—recession—is top of mind for companies around the country. In a Capterra survey of 300 HR leaders in the U.S., 72% say their employer has already started preparing for a possible recession, while 24% plan to start preparing soon.*
As in previous economic downturns, organizations will need to figure out ways to reduce labor costs, including deciding which employees to lay off if it comes to that. Where 2023 differs is that HR is both more strategically involved in these high-level labor decisions and more data-driven than ever before, supported by cutting-edge HR software systems that can aggregate massive amounts of employee information and turn it into actionable insights and recommendations. Read More
Human Vs. Artificial Intelligence: Why Finding The Right Balance Is Key To Success
elcome to the age of blended workforces, where intelligent machines and humans combine to accelerate business success.
In short, now that we have increasingly capable robots and artificial intelligence (AI) systems – capable of taking on tasks that were previously the sole domain of humans – it’s easier than ever for organizations to leverage intelligent machines. But this leaves employers with some major questions to answer: how do we find the right balance between intelligent machines and human intelligence? What roles should be given over to machines? And which roles are best suited to humans? Read More
AI decision automation: Where it works, and where it doesn’t
Some companies are using AI for end-to-end decision-making, but not all decisions can be made without human intervention. Here are some real-world cases.
As artificial intelligence (AI) ascends in the marketplace, the burning question remains as to how far it can be trusted when it comes to the “last mile,” the final decision that follows the analytics and recommendations that AI yields.
… “Not all decisions in organizations can be fully automated, and some of these will require human intervention.” Read More
AI Assesses Alzheimer’s Risk by Analyzing Word Usage
New models used writing samples to predict the onset of the disease with 70 percent accuracy
Artificial intelligence could soon help screen for Alzheimer’s disease by analyzing writing. A team from IBM and Pfizer says it has trained AI models to spot early signs of the notoriously stealthy illness by looking at linguistic patterns in word usage. Read More
Algorithms Are Making Economic Inequality Worse
The risks of algorithmic discrimination and bias have received much attention and scrutiny, and rightly so. Yet there is another more insidious side-effect of our increasingly AI-powered society — the systematic inequality created by the changing nature of work itself. We fear a future where robots take our jobs, but what happens when a significant portion of the workforce ends up in algorithmically managed jobs with little future and few possibilities for advancement?
… How many Uber drivers do you think will ever have the chance to attain a managerial position at the company, let alone run the ride-sharing giant? … There’s a “code ceiling” that prevents career advancement — irrespective of gender or race. Read More
9 Soft Skills Every Employee Will Need In The Age Of Artificial Intelligence (AI)
Technical skills and data literacy are obviously important in this age of AI, big data, and automation. But that doesn’t mean we should ignore the human side of work – skills in areas that robots can’t do so well. I believe these softer skills will become even more critical for success as the nature of work evolves, and as machines take on more of the easily automated aspects of work. In other words, the work of humans is going to become altogether more, well, human. Read More
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