Oct
A Human Center Makes Market Research All The More Powerful
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World
The Future Of Research Is Here
You’ve seen it and there’s no denying it. Industries have been reshaped by the increasing utilization of Artificial Intelligence just in the last few years alone. Promising and delivering speed and optimization at the fraction of the costs and resources, it’s powerful, revolutionary and exciting. And as with any emerging technology, it comes with its own set of anxieties.
In line with its growing popularity and adoption, people in different industries have been expressing nervousness over being replaced in their jobs by AI. Certain repetitive, data-driven tasks are at the greatest risk of being supplanted by AI. However, AI also opens up opportunities to shift focus and upskill the more complex and creativity-driven facets of work roles, creating new jobs or augmenting existing ones.
The research industry is just as impacted by AI’s progressive application. It’s naive to assume that researchers would be replaced wholesale by AI, but there’s more to delivering research results than just gathering and crunching data.
Image: Circe Deyer
Our take on the integration of AI into research
We’ve always maintained that AI is a good advisor, but it’s a poor decision-maker. We’d like to modify that by saying it’s an even worse storyteller, if at all.
Cascade Strategies has been in the market research industry for over three decades now, serving some of the biggest local and international companies. You can say we’ve seen it all in this industry, but we’re just as fascinated as everyone else by the mainstream popularity of AI in the past few years. We’ve applied it in our methodologies, been impressed by its operational benefits and how it changed industries, but in the end, we know truthfully that it is not the end-all, be-all for research work. We believe that AI would serve us better by being a powerful extension of human judgment, creativity, and insight.
AI can be fed large datasets to approximate human thinking, but we believe it can never replicate human perspicacity, the kind of intelligence honed and guided by human values and experience. Take a look at our Expedia Group Case Study where we’ve utilized AI to generate multiple revenue-granting scenarios, then tempered the decision-making process by applying high-level human thinking to craft messaging that resonates with the end-user.
AI-driven research can produce results based on what has come before, but it can never uncover the truly novel, meaningful and resonant insights high-level human thinking unlocks. These are the insights that empower big and sweeping decisions. Data-based results from AI would seem lifeless and unrelatable. But if they are imbued with human interpretation, that output elevates into a masterful narrative that sparks imagination, questions boundaries, and transforms perspectives.
Image: geralt
Featured Image: mohamed mahmoud hassan
Top Image: geralt
Oct
AT&T allowed us to conduct qualitative and quantitative research for them. The result was a key brand insight about the Worry Wort, a kind of subscriber who preferred AT&T over rivals Verizon and T-Mobile for a variety of reasons and tended to stick with AT&T for the long haul. The campaigns built around the Worry Wort allowed AT&T to reduce churn and fend off wireless competitors.
It’s doubtful that submitting the same data to AI would produce a finding as incisive as the Worry Wort. This is something to bear in mind if you’re a telecommunications brand seeking to thrive: human perspicacity counts.
There’s a kind of intelligence AI can’t reach. It has dimension, soul, and human inspiration. In the telecommunications business, we’d do well to remember this as we pour more datasets into the maw of AI. If you’re in the telecommmunications business and need human perspicacity, you might call Cascade Strategies. We can help you see things AI can’t see.
Featured Image: (Public Domain)
Top Image: Brownings at English Wikipedia
Sep
Pan Pacific Hotels allowed us to conduct qualitative and quantitative research for them. The result was a key brand insight about the Cosmopolite, a kind of guest who preferred Pan Pacific lodging even when other hotel offers were better. The campaigns built around the cosmopolite allowed Pan Pacific Hotels to weather economic downturns and pandemics, and even expand into key markets in Asia.
It’s doubtful that submitting the same data to AI would produce a finding as incisive as the Cosmopolite. This is something to bear in mind if you’re a hospitality brand seeking to thrive: human perspicacity counts.
There’s a kind of intelligence AI can’t reach. It has dimension, soul, and human inspiration. In the hospitality business, we’d do well to remember this as we pour more datasets into the maw of AI. If you’re in the hospitality business and need human perspicacity, you might call Cascade Strategies. We can help you see things AI can’t see.
Featured Image: Saksham Vikram
Top Image: Alix Lee
Sep
Achieve Breakthroughs By Tapping Into Your Primal Intelligence
jerry9789 0 comments artificial intelligence, Burning Questions
Is Artificial Intelligence going to be the be-all, end-all for decision-making, problem-solving and innovation? If AI is faster, more logical and more efficient than humans, why hasn’t it overtaken us already? Is there a way for human genius to gain the edge over AI?
Yes, AI has changed the way we’ve done things these last few years – optimizing and streamlining processes to improve efficiency and effectiveness while maximizing output and in some cases, reducing costs. AI thrives in a production environment with defined datasets, but take away all that reliable data and introduce new variables, and it crumbles.
AI can generate art and stories, but it does this based on the data it was fed and trained on. It’s truly incapable of producing anything genuinely novel from outside that frame. This means it has the potential to suffer in a self-loop of homogeneous and biased outputs over time, building towards incoherence.
In a world that is increasingly being taken over by AI processes and outputs, recognizing and understanding this limitation is going to help human intelligence find its place and continue to thrive and evolve. In fact, just as AI gained mainstream popularity these past few years, another type of human intelligence has captured the attention and imagination of researchers – and the U.S. Army at the same time.
Image: Lukas
What Is Primal Intelligence?
Ohio State University professor Angus Fletcher, along with other researchers at Ohio State’s Project Narrative, started to investigate in 2021 something called “primordial brainpower” that reportedly drives human intuition. Their research led them to something they call Primal Intelligence, a kind of “natural cleverness” by humans that can be strengthened through training, but which AI can’t replicate.
Professor Fletcher describes Primal Intelligence as part of our lost nature and a key to activating intuition, imagination, emotion, and common sense. The U.S. Army Special Operations then adopted primal training for its most classified units and according to Professor Fletcher, Special Operators saw the future faster, thought more quickly, acted more swiftly, and healed more rapidly from trauma. After the Army authorized trials on civilians such as entrepreneurs, doctors, engineers, managers, coaches, teachers, investors, and NFL players, they found their leadership and innovation significantly improved. These civilians coped better with change and uncertainty, and experienced less anger and anxiety. The Army subsequently provided primal training to college and K–12 classrooms with students as young as eight, and they reported substantial beneficial effects from the training. In 2023, the Army awarded Professor Fletcher the Commendation Medal for his research on retraining the human mind.
Professor Fletcher’s research has been endorsed by renowned psychologists, neuroscientists, and doctors. He has received support from major institutions such as the National Science Foundation. He also wrote the book Primal Intelligence: You Are Smarter Than You Know, from which the following five key insights for sharpening our primal intelligence are derived.
Image: Alana Jordan
1. Exceptional Information
Special Operators “see” or anticipate the future faster than other soldiers on the battlefield, thanks to their unusually high level of intuition. But how does one improve their intuition?
To begin with, you’ll need to dissociate intuition from the decades-old concept that intuition is just mere pattern matching. The aforementioned Operators have trained their brains to find what the Army has dubbed “exceptional information.” Succinctly put, exceptional information is an exception to a previously established rule; it’s the opposite of a pattern because it’s the breaking of a pattern.
Young children score high on intuition but lower at pattern matching because their brains are focused more on unusual details than on familiar patterns. Training your brain to spot exceptions rather than thinking in patterns can help improve your intuition.
Travel or go on trips to immerse your brain in places that break the pattern of your regular life. Reading the works of authors like Shakespeare can also help improve intuition because of characters who are exceptions to traditional narrative tropes, like Hamlet the deep-thinking action hero or the cold and scheming Cleopatra who possesses a loving heart. Known Shakespeare readers who were able to anticipate the future by spotting exceptions range from Nikola Tesla with his AC motor, Marie Curie with radioactivity, and even Vincent van Gogh and his use of aquamarine.
Image: Donald Tong
2. Rethinking Optimism
Optimism pushes us to take on chances which could lead to growth, but why do many people fall back into pessimism? Why do we need to remind ourselves that optimism works better than pessimism instead of instinctively switching to the former frame of mind whenever something new or unusual comes up? Why is optimism this fragile in our minds?
This has something to do with how we think of optimism. We’ve been taught that optimism is “this will succeed,” when “this can succeed” is much more powerful and stronger. Instead of convincing us that this will succeed, we remember that we can succeed.
Remembrance over visualization. Special Operators call this method antifragile because remembering that one time in the past when you’ve been successful is more resilient than magically thinking of achieving success. Building your optimism on the foundation of faith where you’ve succeeded one time no matter how many times you fail can be all you need to keep on going. This is an improvement over being buoyed by the hope that you can succeed, but having your confidence eroded when you don’t.
Image: Kaboompics.com
3. Thinking In Story
In new situations with little to no precedent values (where AI falls apart), how are Special Operators not only able to pull through but also excel?
We have to remind ourselves that the human brain features more than one type of intelligence. While it evolved over a million years with the capacity to think logically and process data from which computers were modeled, the human brain also developed narrative cognition or simply put, the ability to think in story.
Thinking in story means the brain sees the “movement” of story, from beginning to middle to end, with room for imagination to explore possibilities and wisdom to sensibly tie things together. AI has the ability to generate story plots and images from datasets, but it still doesn’t read the story. It’s still our human brains that instill story and meaning to these generated plots and images.
High-data environment and conditions might not be conducive for thinking in story, but it finds its place in volatile and uncertain situations. Special Operators who performed well in volatility were found to have brains proficient at thinking in story.
Image: cottonbro studio
4. Empowerment Through Role-playing
Anger and anxiety are physiological indicators of a threat response. So what’s the best way to mitigate the brain’s threat response? Removing the threat, usually with outside force, might spring to mind but what if we tell you that conjuring a gameplan with your brain to deal with the threat is more effective?
That’s exactly how Special Operators function. Instead of avoiding threats, they advanced toward the threats and they do this without feeling anxious or angry. That’s because these Operators have trained their brains to imagine plans for dealing with threats. And they train their imagination by engaging in role-playing exercises.
Outside of Special Operations, role-playing can be taught to regular people or students by taking part in arts and humanities activities such as theater, literature, and history. The key is to be able to imagine oneself as somebody else in another place or situation, engaging the brain’s ability to imagine plans for handling threats.
Image: geralt
5. Possibility Over Probability
How do you train people so that you produce leaders and not just managers? Focus your training on expanding their ability to think not in probability but in possibility.
What’s the difference? Probability is calculated or based from past events while possibility assumes an event that hasn’t happened could happen. Probability is employed by statistics and computer AI while possibility empowers story and imagination. With a fundamentally different mental process involved, possibility engages original thinking, enterprise, and initiative: key mental qualities of entrepreneurs and leaders in general.
You can expand your sense of possibility by stimulating your brain’s premotor cortex and boosting your practical imagination with realistic tales of make-believe. The Wright brothers read the creative works of Charles Dickens and Mark Twain, while Special Operators prefer novels set in the near future or in a different culture.
Image: Katrin Bolovtsova
Cascade Strategies and Primal Intelligence
Cascade Strategies has not only been advocating for the “appropriate use of AI” but has also been consistently pushing for the appreciation of high-level human thinking, especially when it comes to market research. This research on primal intelligence underscores our stance on the irreplicable and inimitable merits of human intelligence. We believe there are values and experiences humans bring to the table that AI simply cannot match. We’ve always believed that breakthroughs in market research can only be unlocked only with the proper application of human intelligence. To learn more about how our thinking can help you with your brand development and market research needs, please contact us here.
Additional Reading:
Why AI Will Never Defeat Primal Intelligence
‘Primal Intelligence’ Review: Why Brains Are Better
Featured Image: johnhain
Top Image: geralt
Sep
Some years ago, Publix Supermarkets allowed us to conduct qualitative and quantitative research for them. The result was a key brand insight about a kind of consumer called the Reluctant Shopper. Despite the ironic name, this kind of consumer hewed more closely to the shopping experience Publix offered than to competitive shopping experiences. The campaigns built around the Reluctant Shopper helped Publix weather the storm of competition from well-heeled operators like Walmart. Winn-Dixie, a much larger chain with many more stores, perished.
We recently asked Gemini to review the same dataset and report on it. Gemini provided a sparkling and quite accurate report on the data but perceived nothing about the Reluctant Shopper. This is something to bear in mind if you’re a consultant advising a brand on how to thrive: perspicacity counts.
There’s a kind of intelligence AI can’t reach. It has dimension, soul, and human inspiration. We’d do well to remember this as we pour more datasets into the maw of AI. If you’re a consultant and need perspicacity, you might want to contact Cascade Strategies. We can help you see things AI can’t see.
Image: Harrison Keely
Aug
Can Synthetic Respondents Take Over Surveys?
jerry9789 0 comments artificial intelligence, Burning Questions
What Are Synthetic Respondents?
AI has increased operational efficiency by streamlining knowledge bases and shortcutting processes so it’s no surprise people and companies are looking for more ways for its application. For market research, one curious consideration is whether it could take over surveys, essentially by replacing actual respondents with synthetic respondents.
Also known as virtual respondents, digital personas, and Virtual Audiences, synthetic respondents are individual profiles constructed by Large Language Models (LLMs) from real or simulated data. Ideally, the data or descriptions used to generate these profiles come from previously conducted surveys and are combined with individual-level demographics, attitudes and behaviors.
Using these synthetic respondents over real respondents could benefit your research with speed, accuracy and cost savings, at least according to their advocates. Basically, you just need to conduct one survey and from the profile description or data you gathered from the actual respondents, you’re able to generate results from the constructed individuals over and over for succeeding studies and research.
Testing Synthetic Respondents
While synthetic respondents could accurately represent real respondents, relying exclusively on the results from these AI-based individuals may not be entirely beneficial. A webinar hosted by Radius Global took a closer look at the potential of AI-generated synthetic respondents through three case studies of quantitative concept testing, quantitative communications research, and qualitative communications research.
Aggregate results for the concept tests involving game controllers indicate somewhat strong similarities between the results of the real and synthetic respondents. This extends to the results from the quantitative communications research when it comes to the believability of statements on the benefits of milk, although there were some differences. The differences were much more pronounced though when it comes to surprise over the same statements, and there was incongruence when considering how each statement could possibly increase milk consumption.
The qualitative communications research was seeking in-depth insights into women’s needs, perceptions, and preferences for running a race or marathon, with the feedback gathered meant to be used for creative content. Personas were constructed from the profiles of six women aged between 18 and 64 years old who ran at least once in an average week. They had an LLM assume each persona to allow a comparison between findings from real participants to synthetic respondents.
They found that while both real and synthetic respondents have somewhat similar responses when it comes to functional aspects as goals for women in general pursuing fitness, the AI responses lacked emotional expressions. There are also little differences in the synthetic respondents’ responses despite having different profiles, and there was even a lack of subtle differences.
As for concerns among women who are aspirational marathon runners, the synthetic personas were consistent in their responses while the real respondents provided more nuances, variety, and perspectives more prevalent among women.
Synthetic Respondents vs. Real Respondents
Synthetic respondents appear to be useful if you’re evaluating existing ideas and concepts; however, if you’re looking for “breakthroughs” or essentially new insights you would’ve never arrived at had you not performed the case study or research, you would need to engage with real respondents, relying exclusively on their results or combining them with that of synthetic respondents. Yes, there could be cases where synthetic respondents could be used, but the results must be extensively validated. It would also require increasing the efficiency of how data used to construct these individuals are analyzed in addition to enhancing the quality of the data and information gathered for these profiles through thorough screening, intelligent probing, and smart choice models.
There is a place for synthetic respondents in market research, but as another tool in a researcher’s toolbox. They won’t be taking over surveys or replacing actual respondents wholesale anytime soon, it seems, as that elusive “Eureka” moment researchers seek is inherently tied to the nuances and perspectives of human emotion and experience you simply can’t construct.
Photo courtesy of Pavel Danilyuk
Jun
How Great Research Helps Financial Services Companies
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World, Burning Questions
From maintaining loyalty and fostering customer relationships to focusing marketing messages on the most profit-optimal consumer, great research is helping Financial Services companies identify not only their best customers and prospects but also their needs and why they prefer their brand over others. This is done through a high-quality segmentation study and persona development, which break a company’s market into different groups so that different strategies for marketing to these groups can be leveraged. The main reason a company wants to complete market segmentation research is so they can gain actionable insights, like how to sell more of their product or services.
Take for example, Banner Bank for whom Cascade Strategies developed a brand model which identified “Strivers” as the primary segment they should focus on. The bank initiated special promotions and appeals featuring the products of greatest interest to Strivers. A Striver-specific ROI program was developed to measure the degree of program success. Modeled indices were used to set Striver product targets by branch. After 2 years of activity, Banner Bank exceeded all key Striver product targets system-wide.
Read about our approach to high-quality brand development research here.
Another example is the case of Capital One where they needed help trying to identify the “persona” or psychographic type most interested in adopting a certain mobile app for personal investing. We conducted in-person depth interviews with “mobile-minded consumers.” We also conducted an unpacking session with Capital One staff where individual staff members were given assignments to review videos and be prepared to discuss key traits and behaviors of respondents, such as outlooks, investing styles, goals, worries, needs, plans, and so forth.
We identified that the “Empath” is the most interested in adopting a certain mobile app for personal investing. The “Empath” persona is fairly immersed in pragmatic thinking and probably best understands the possibilities for “thinking” or guidance apps, allowing Capital One to focus their brand campaign effort on the needs of this psychographic type. The net result was a highly successful new product introduction.
Read about our approach to segmentation studies and the development of brand personas here.
Image: Cottonbro Studio
“But wait, can’t AI do this?” you may ask. While there is a faddish and hype-driven tendency to turn quickly to AI for short-cuts in market research, AI cannot yet fully replicate the deep interpretive and intuitive skills of the human brain, especially the right brain (the nonrational side). Moreover, effective AI deployment requires human supervision and involvement as final arbiter of how the outcomes will be leveraged.
As you can see, market research results as good as the examples above come from human-centered thinking, the kind that allows brands to break past ordinary bounds and achieve true excellence. It’s this kind of extraordinary thinking that Cascade Strategies has consistently provided a long list of US and international clients for 33 years.
Feel free to reach out to us to discuss your needs at https://cascadestrategies.com/contact-us/
Jun
AI In Retail: Market Research In Play
jerry9789 0 comments artificial intelligence, Brandview World, Burning Questions
Perhaps there is no better example of market research in play than the utilization of artificial intelligence in retail. AI has disrupted industries after gaining traction and mainstream popularity just in the last few years, but its transformative power is arguably most visible in the retail landscape. From personalized shopping experiences to visual merchandising, we’ll take a look at the impact AI has had so far not only on the retail industry, but also on retail market research today.
Personalized Shopping Experience
We’re now at the point where customers expect brands to not only acknowledge them but understand and cater to their preferences. Retailers have traditionally prized such insights as vital to conversion rates, marketing campaigns, and brand loyalty. AI is in the perfect position to deliver these insights at a more incisive and actionable level. By analyzing a customer’s data such as browsing history, purchasing behavior, preferences, wishlists, and shopping cart items, AI is able to create personalized and tailored recommendations that help simplify the shopping process and guide consumers toward better purchasing decisions, thus contributing to a more enjoyable shopping experience. In fact, a McKinsey report found that 35% of Amazon purchases were due to personalized recommendations.
Aggregate customer data of this type helps shape the direction of a brand’s marketing campaign by identifying and homing in on the ideal customer for a particular product or service, reducing traditional marketing costs while optimizing conversion. This also extends to lead generation as the customer data gathered from transaction history and personal preferences can help form a prospect list for future products and campaigns.
The extensive data of browsing and purchase history along with personal preferences also benefits product searching and product description generation. The former means that AI is able to produce highly accurate site search results based on context and intent even if a customer struggles with the appropriate keywords for the product they’re looking for. The latter saves time and increases efficiency by generating comprehensive, unique and engaging product descriptions that are also SEO-optimized, especially when combined with product image analysis and natural language processing.
Loyalty and rewards programs can also be made more effective with incentives and exclusive deals aligned to a customer’s taste and preferences over generic, random, and unenticing offers, encouraging engagement and increased or repeated visits or spending while also improving retention.
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Dynamic Pricing and Promotions
Retailers are now able to unlock another advantage with AI through dynamic pricing strategies and promotions. This ability allows retailers to adjust pricing based on real-time analysis of market conditions, competitor pricing, inventory levels, consumer demand and behavior, just to name a few factors. This can be done not only by branch or region but also on an individual level, and can take advantage of peak hours, promotional activities or clearance sales. Dynamic pricing allows retailers to maximize profits, maintain competitiveness as well as engage or retain customers looking for better deals.
Predictive Analytics for Inventory Management and Demand Forecasting
It’s important for retailers to optimize inventory management to prevent overstocks or stockouts, maximizing sales while minimizing losses. Step away from those time-consuming and fallible spreadsheets, though; AI-powered predictive analytics is now the key tool in any retailers’ arsenal for demand forecasting. By analyzing sales data based on purchasing history, market trends, inventory levels, consumer behavior and preferences, retailers are able to predict future trends to improve operational efficiency by making smart decisions with stock planning and supply chain management. This is further augmented by employing cameras, digital sensors or smart shelves to monitor inventory levels in real-time, allowing store staff to replenish shelf stock from the supply room when needed.
In-store Navigation
AI-powered chatbots and virtual assistants are helping improve customer satisfaction by assisting and guiding with site navigation and other queries, but they’re not limited to the online realm as they can also be used by physical locations. Aside from simple navigation instructions, in-store navigation can be taken to the next level with an AI-generated foot trail map optimized with the best path for navigating across the store based on the items on the customer’s shopping list.
AI can also provide valuable feedback and insights for optimizing store layout and foot traffic from the customer movement patterns it captures and analyzes. These insights can also help with the placement of particular products a store would like to promote or increase visibility of.
Copyright: TyliJura
Visual Merchandising
The days of static print and basic digital signage are slowly going out of style; retail visual merchandising is now evolving to tell dynamic and engaging brand narratives that extend from the purely informational to the experiential. Powered by AI, retail experiences now allow brands to connect and resonate with consumers more effectively than before with visual merchandising content that’s not only relevant to the buyer’s journey but also convey a strong and intelligent creative direction.
Imagine AI-powered signage that reacts or adjusts content in real time to help you with your purchasing decision at a store, especially at times when you’re looking at the shelf or aisle and not sure which brand to pick. Dynamic visual merchandising can highlight products based on current popularity or stock to influence your choice. During peak hours, this could mean you’re able to get your hands on the best-selling item before it runs out or select the product with enough available stock if you need to meet a certain quantity. Unlike manual content, which could outdate if the product presented has stocked out, AI-driven merchandising can present alternatives and introduce new brands which would otherwise have been unexplored or missed by consumers.
Emerging technologies such as virtual try-on and augmented reality (AR) add another layer to how customers interact with products. The former uses AI to simulate how clothing or accessories would look like or fit on a customer, while AR helps visualize products in different settings or styles. These technologies help reduce return rates and drive customer satisfaction and brand loyalty.
Copyright: TyliJura
We’ve touched on only a few of the current and noteworthy applications of AI in retail. There are many others, and more will likely be added in the near future as this technology continues to evolve. Embracing AI can reward a brand or company with competitive advantages and success, but the rewards aren’t necessarily reaped overnight. AI saves time, reduces costs, and optimizes sales and operations; but companies need to be strategic, adaptable, innovative, and ethical when harnessing this technology. Not only would a retailer need to invest time, effort, and resources to build the extensive data and foundational systems of their AI infrastructure, they would also need to gain an understanding of how everything connects and works with one another, as well as how it all aligns with their company’s goals.
If you’re a retail company looking for help in adopting AI in the best way possible, Cascade Strategies can assist you in this endeavor. Not only are we well versed in AI technology, we are advocates of “appropriate use of AI.” We appreciate the advantages and benefits AI brings, but we firmly believe that it’s at its most effective when harnessed and guided by human values and experience. Contact us today to learn how Cascade Strategies can help your company enrich retail operations and the shopping experience you offer to your customers with AI.
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Apr
AI’s Impact On Critical Thinking and Learning – What Studies Are Saying So Far
jerry9789 0 comments artificial intelligence, Burning Questions
Generative AI and Critical Thinking
On our last blog, we touched on two studies suggesting that Generative AI is making us dumber. One of those studies, which was published in the journal Societies, aimed to look deeper into GenAI’s impact on our critical thinking by surveying and interviewing over 600 UK participants of varying age groups and academic backgrounds. The study found “a significant negative correlation between frequent AI tool usage and critical thinking abilities, mediated by increased cognitive offloading.”
Cognitive offloading refers to the utilization of external tools and processes to simplify tasks or optimize productivity. Cognitive offloading has always raised concerns over the perceived decline of certain skills — in this instance, the dulling of one’s critical thinking. In fact, the study found that cognitive offloading was worse with younger participants who demonstrated higher reliance on AI tools and less aptitude when it comes to their own critical thinking skills.
Conversely, participants with higher educational backgrounds showed better command of their critical thinking no matter the degree of AI usage, putting more confidence in their own mental acuity than the AI-based outputs. Aligning with our advocacy for the “appropriate use of AI,” the study emphasizes the importance and appreciation of high-level human thinking over thoughtless and unmitigated adoption of AI technology.
Copyright: jambulboy
Generative AI and Learning
In truth, a number of earlier studies have revealed that the arbitrary adoption of AI tools can be detrimental to one’s ability to learn or develop new skills. A 2024 Wharton study on the impact of OpenAI’s GPT-4 demonstrated that unmitigated deployment of GenAI fostered overreliance on the technology as a “crutch” and led to poor performance when such tools are taken away. The field experiment involved 1,000 high school math students who, following a math lesson, were asked to solve a practice test. They were divided into three groups, with two of these groups having access to ChatGPT while the third had only their class notes. One group of students with ChatGPT performed 48 percent better than those without; however, a follow-up exam without the aid of any laptop or books saw the same students scoring worse by 17 percent than their peers who had only their notes.
What about the second group with the GenAI tutor? They not only performed 127 percent higher than the group without ChatGPT access on the first exam, but they also scored close to the latter during the follow-up exam. The difference? Sometime down the line of their interactions, the first group with ChatGPT access would prompt their AI tutor to divulge the answers, resulting in an increased reliance on GenAI to provide the solutions instead of making use of their own problem-solving abilities. On the other hand, the other group’s AI tutor version was customized to be closer to how real-world and highly effective tutors would interact with students: it would help by giving hints and providing feedback on the learner’s performance, but it would never directly give the answer.
Similar tests with a GenAI tutor in 2023 studied the same issue of AI dependence and the value of careful deployment of AI tools. Khanmigo, a GenAI tutor developed by Khan Academy, was voluntarily tested by Newark elementary school teachers, who belong to the largest public school system in New Jersey. They came back with mixed results, with some complaining that the AI tutor gave away answers, even incorrect ones in some cases, while others appreciated the bot’s usefulness as a “co-teacher.”
Other studies regarding the effectiveness of AI tutors have shown increases in learning and student engagement. These studies have also shown that GenAI can help reduce the time it takes to get through learning materials compared to traditional methods. One study that extolled the benefits of GenAI tutors involved Harvard undergraduates learning physics in 2024, and similar to the third group in the Wharton research, the AI was prevented from directly providing the answer to students. It would guide the student throughout the learning process one step at a time, providing incremental updates of the student’s progress, but never outright telling them the answer. There are merits to the idea of Generative AI as a teaching assistant, but it serves students better when it is positioned to engage one’s attention and abilities rather than induce dependence on it to generate the answers.
Copyright: Only-shot
Can We Use GenAI Without Making Us Dumber?
These studies shed light on how we should approach AI solutions and development, whether the end product is being deployed in learning, productivity or other relevant applications. Beyond thoughtful planning and considerations on how AI tools would be deployed, there should be a focus on engaging the human faculties involved, with safeguards empowering man throughout the entire process instead of letting the machine take over the process wholesale. AI technology is developing rapidly, but we can keep pace and remain reasonable as long as human engagement and empowerment is kept at the core of its utilization and adoption.
Amid contemporary fears that anyone could be replaced anytime by AI, these studies highlight the importance of how vital and interconnected the human factor is to the effective deployment and development of AI tools. One could be content with the constant and consistent output AI tools generate, but progress is only possible when competent human minds are involved in the process and direction. Students can easily find answers with AI tools at their disposal, but why not advance their understanding of how solutions are formed with engaging and relatable AI-powered educational experiences? High-level human thinking grounded by values and experience can’t be replicated by machines, and perhaps there’s no better time than now to incorporate it into the heart of the AI revolution.
While AI development hopes that optimization and automation free the human mind to go after bigger and more creative pursuits, we here at Cascade Strategies simply hope that humanity emerges from all of these advancements more and not less than what it was when we entered the AI revolution.
Additional Reading:
Why AI is no substitute for human teachers – Megan Morrone, Axios
AI Tutors Can Work—With the Right Guardrails – Daniel Leonard, Edutopia
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Mar
Are We Getting Dumber Because of AI?
jerry9789 0 comments artificial intelligence, Burning Questions
Is Generative AI making us dumber? Two recent studies suggest so.
A study published early this year titled “AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking” showed that growing dependence on AI could lead to a decline in critical thinking. Submitted by Michael Gerlich of the SBS Swiss Business School, the study was based on surveys and interviews of 666 UK participants from different age groups and academic backgrounds. The problem is more pronounced with younger participants who demonstrated increased reliance on AI to perform routine tasks and scored lower when it comes to critical thinking than their older counterparts.
More recently, a study by Microsoft and Carnegie Mellon University shared similar findings that the more workers depended on AI for their work, the duller their critical thinking becomes. The study surveyed 319 knowledge workers who used generative AI at least once a week and examined how and when they apply AI or their critical skills when performing tasks. The more faith the participant put in genAI to produce acceptable outcome, the less they use their critical thinking skills. On the other hand, participants who have higher confidence in their abilities than that of AI’s are found to exercise their critical thinking more out of concerns over unintended and overlooked machine output.
Copyright: Tara Winstead
What is Cognitive Offloading?
Both studies are linking overreliance on AI with cognitive offloading, which is when someone utilizes external tools or processes for completing tasks, resulting in their reduced engagement with deep, reflective thinking. Yes, AI is improving efficiency and saves time and financial costs, but these studies are suggesting that it could make humans less smart over time.
However, cognitive offloading isn’t new as it existed in a variety of forms throughout time, such as using a calculator instead of performing mental mathematics or simply making a grocery list instead of memorizing all the items you need to buy. It’s no surprise then that there are questions about the merits of the studies, such as self-reporting bias or how critical thinking was measured. Forbes suggests that AI isn’t making us dumb but lazy, while another emphasizes that in order for there to be harm to one’s critical thinking abilities, one must have critical thinking to begin with.
Copyright: Pavel Danilyuk
Rethinking AI Development
Nevertheless, these studies contribute to the conversation regarding the direction of genAI development, now with the nuance of being mindful and respectful of its human users’ intelligence and faculties. Recommendations include rethinking AI designs and processes which incorporates and engages human critical thinking. They’re helping bring back focus to AI serving as a tool augmenting instead of overtaking human capabilities.
For us at Cascade Strategies, we’re glad that these studies have renewed awareness and appreciation of human intelligence and creativity. Our world could’ve easily devolved into settling for more of the same output so it pleases us to learn that more voices are becoming advocates and proponents not only of the “appropriate use of AI” but also of high level human thinking.
Featured Image Copyright: Alex Knight
Top Image Copyright: Tara Winstead
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