The Things AI Can’t Teach: The Value of Huamnity
Reference:
DeSchryver, M., Henriksen, D., Leahy, S., & Lindsay, S. (2024). Beyond automation: Intrinsically human aspects of creativity in the age of generative AI. Central Michigan University & Arizona State University.
Annotation:
In a world where GenAI is getting better at writing, designing, analyzing, and even “creating,” this article asks a surprisingly grounding question:
What parts of creativity are still fundamentally human and why should we care?
The authors argue that while AI can mimic creative output, it cannot replicate the experience of creativity. They highlight six intrinsically human creative capacities:
Curiosity
Intuition
Mindfulness/Patience
Imagination
Empathy
Embodied Thinking
Each of these capacities is shown to stem from lived experience, emotion, bodily awareness, and cultural or ethical context, things AI cannot meaningfully possess.
The article concludes with a bold call for education and training programs to prioritize these human strengths, especially as workplaces adopt more AI tools. What makes this article compelling for L&D practitioners is how clearly it demonstrates that the deepest forms of learning transfer rely on human senses and embodied cognition, not just content delivery.
Even in corporate e-learning or hybrid training, learners use their:
sense of movement
perception of space
emotional resonance
curiosity-driven discomfort
intuitive pattern recognition
empathetic social awareness
reflective stillness
These are not “nice to have” elements. They are the mechanisms through which information becomes memory, memory becomes understanding, and understanding becomes real-world behavior change. AI can support training, but it cannot replace these body-anchored processes.
The article’s strengths lie in its clear framework of six human creative traits, which provides educators with a practical structure for evaluating AI’s role in learning environments. It also connects theory to real educational practice, offering concrete implications for classrooms and instructional design.
The authors thoughtfully distinguish between AI’s ability to mimic creative outputs and the uniquely human experience of creativity, and they incorporate cultural and embodied perspectives that highlight AI’s current limitations. However, the article can be dense at times, relying heavily on academic theory, which may feel abstract for practitioners seeking immediate application. Its cultural analysis leans largely on Western research, leaving room for broader global insight, and while it acknowledges that AI may evolve toward more human-like traits, it stops short of fully exploring emerging areas such as embodied robotics and multimodal agentic systems.
The article does not explicitly frame creativity in terms of the body’s senses—but it could, and doing so makes the implications for learning transfer even more powerful.
Below is a reframing of the six traits through the lens of innate human sensory faculties, capacities AI cannot authentically replicate.
1. Curiosity → The Sense of “Cognitive Hunger”
Linked to dopamine systems, orientation reflexes, and the brain’s drive toward novelty.
In training, curiosity sparks attention — the first gateway to learning transfer.
2. Intuition → Gut Sense (Interoception) + Pattern Experience
Humans feel intuition physically: tightness, ease, resonance.
AI has no interoceptive system and no lived experiences to shape intuitive judgment.
3. Mindfulness/Patience → Temporal Sensory Awareness
Humans perceive time through emotional and physiological regulation.
Incubation, the moment when learning quietly consolidates, depends on embodied calm, not computational speed.
4. Imagination → Mental Imagery + Visuospatial Processing
When we imagine, sensory cortices light up as if we are seeing or hearing.
AI recombines text and image data but does not experience imagery.
5. Empathy → Emotional Resonance (Affective Sensing)
Humans detect microexpressions, tone, posture, and relational energy unconsciously.
AI can label emotions but cannot feel them or use them for moral discernment.
6. Embodied Thinking → The Entire Sensorimotor System
Creativity is deeply body-based: gesture, movement, rhythm, weight, balance.
These physical cues are essential for problem-solving, skill acquisition, and long-term memory encoding.
New Ways to Engage Remote Learning
Reference:
Dirkin, K., Hain, A., Tolin, M., & McBride, A. (2020). OMMI: Offline MultiModal Instruction. Central Michigan University & Dare County Schools.
Annotation:
If you have ever tried to run training for a decentralized workforce, especially sales teams who seem to always be on the road, you know the struggle. WiFi drops. Airports are loud. Hotel connections crawl. And yet these employees have the greatest need for frequent learning because success in sales depends on constant skill improvement. That is exactly why OMMI jumped out as such a refreshing idea.
The Offline Multimodel Instruction (OMMI) model, originally built to support students without broadband access, is all about sending rich, interactive learning experiences without relying on the Internet. This is done through something called datacasting, which delivers videos, documents, and other multimodal content straight to a device even if the user has zero connectivity.
The fun part of OMMI is how simple but clever it is. Instead of reinventing the wheel, it repurposes everyday tools that already exist on a device to mimic interactive digital learning. Think PowerPoints that behave like mini websites, Word documents with layered clickable elements, and packages of media organized into a weekly learning hub the authors call an anchor document. The whole idea is that offline learning does not have to be boring worksheets. It can be designed to feel interactive and intentional even when it arrives through a one way delivery system.
Now picture how this translates to a remote sales workforce. Sales teams often squeeze learning into airplanes, Uber rides, hotel rooms, and fifteen minute breaks between client visits. They need training that is portable, reliable, self paced, and available without a perfect Internet connection. OMMI offers a way to package skill boosters, micro lessons, role play prompts, and scenario based challenges in a format that they can always access no matter how chaotic their travel schedule gets.
A sales rep could receive a weekly module that includes short videos, interactive exercises built inside slides, and a performance task like drafting a product pitch or analyzing a customer scenario. They do the work offline and upload it whenever they finally get stable connectivity again. This is exactly the kind of system Allegiant Professional Resources can leverage for companies that want to keep their sales staff sharp without forcing everyone into routine Zoom sessions or LMS logins.
Allegiant could design OMMI style modules that mirror the realities of sales work. For example, a “road ready” toolkit for new features, a rapid update package before a product launch, or protocol based reflection activities that help salespeople strengthen their pitch structure and questioning strategies. Because OMMI encourages balanced assessment, Allegiant can design tasks that show real learning instead of relying on simple quizzes. Offline pitch recordings, annotated product sheets, or quick customer mapping exercises can all be part of a multimodal package that requires no WiFi but still drives real capability improvement.
In short, OMMI takes the pressure off connectivity and puts the focus back on learning. For decentralized workforces, especially those with heavy travel demands, this approach can make professional development feel more accessible and more human. And for Allegiant, OMMI opens up a path to deliver high quality learning experiences that follow salespeople wherever the job takes them.
Building the Path to Innovative Employees
Reference:
Glăveanu, V. P. (2020). A sociocultural theory of creativity: Bridging the social, the material, and the psychological. Review of General Psychology, 24(4), 335–354.
Annotation:
Glăveanu advances a comprehensive sociocultural theory of creativity that moves beyond individualistic models and instead situates creativity within the dynamic interplay of social context, material environments, embodied action, and cultural tools. The article challenges traditional cognitive-only explanations and proposes the Perspective–Affordance Theory (PAT), emphasizing that creativity emerges when people shift perspectives, engage with others, explore alternative ways of acting, and perceive new affordances in their environment. Creativity is framed not as an innate trait but as a relational, developmental, and context-dependent process shaped by interactions, dialogue, and the physical tools and spaces individuals work within.
Glăveanu’s framework is particularly valuable for the professional development sector because it recognizes that learning and creative problem-solving are highly dependent on context, tools, and modes of interaction, all of which can be barriers or catalysts for neurodivergent employees. The article subtly highlights how creativity is fostered through multiple perspectives, flexibility in interactions, and diverse ways of engaging with material environments, which aligns strongly with the learning needs of neurodivergent adults who may process information differently or thrive with alternative formats of communication and collaboration.
In asynchronous and hybrid work environments, where many neurodivergent employees may struggle with reduced social cues, inconsistent feedback loops, or rigid digital tools, Glăveanu’s emphasis on dialogue, affordances, and repositioning directly supports the need for more adaptive learning structures. His theory reinforces that employees learn best when they engage with materials hands-on, have opportunities to shift roles, and when learning platforms allow for exploration rather than one standardized pathway. These insights provide an evidence-based rationale for designing multi-modal, flexible professional development experiences that accommodate varied cognitive styles.
Allegiant Professional Resources focuses on helping companies elevate employee skills through inclusive, targeted professional development. Glăveanu’s work provides a strong theoretical grounding for Allegiant’s approach by illustrating that meaningful learning, particularly for neurodivergent adults, requires environments that support varied perspectives, adaptive tools, and opportunities for creative interaction rather than one-size-fits-all instruction.
His theory supports Allegiant’s efforts to:
build learning programs that incorporate multiple modes of engagement,
design asynchronous content with clear affordances that help learners explore and self-direct,
create social learning opportunities that allow for perspective-sharing without overwhelming participants,
and guide employers in crafting hybrid work/learning environments that reduce barriers for neurodivergent thinkers.
Overall, Glăveanu’s sociocultural perspective offers a research-backed justification for Allegiant’s mission to create flexible, inclusive, creativity-enhancing professional development pathways that improve skill-building outcomes for all employees, regardless of neurotype.
AI as the New Workplace Assistant—Promise, Limits, and Practical Realities
As organizations increasingly experiment with AI tools to answer employee questions, interpret policy documents, or guide internal procedures, it is tempting to see AI as a kind of universal workplace assistant: always available, endlessly patient, and capable of reducing administrative burden. But this week’s readings reminded me that using AI as a catch-all solution requires a far more grounded approach. Nemorin et al. (2023) highlight how AI is often surrounded by inflated promises, and this made me more cautious about positioning an AI assistant as a complete replacement for human judgment. Just the way that these AI bots take things so literally makes me think of the old Amelia Bedelia books!
If an internal AI tool provides incorrect information about procedures or compliance requirements, the consequences can be far more serious than a simple technology glitch. The authors also note that AI hype often conceals deeper issues related to privacy and surveillance, which pushed me to consider how internal search tools might inadvertently track or profile employees based on the questions they ask. This may inherently make the AI assistant bias as it collects information on the employee population and the types of questions they may be asking. Can you imagine an AI chatbot telling a high-performing employee they should just quit?
Similarly, Sofia et al. (2023) argue that AI is reshaping workforce expectations by creating constant demands for reskilling. This made me rethink the assumption that AI assistants automatically reduce workload; instead, employees need training to use these tools effectively and to understand their limitations, especially when the AI is interpreting policies or guiding procedural decisions. Their discussion on employee trust also resonated with me. Deploying AI internally is not just a technical decision, it is a cultural one. Employees are far more likely to rely on an AI assistant when the organization communicates clearly about how it works, what data it uses, and where human oversight still matters.
Touretzky et al. (2019) reinforce this human-centered approach by emphasizing the importance of AI literacy. Their argument that foundational AI understanding is essential made me realize that workplace AI assistants should not merely give answers but should support the development of employee judgment. When people understand how AI models process information, they become more discerning and less likely to accept outputs uncritically. The authors’ focus on ethical reasoning also shaped my thinking about internal AI tools. If an AI assistant is delivering guidance on workplace policies, the organization has a responsibility to ensure the system does so ethically, accurately, and in ways that support, not undermine, employee autonomy. Sometimes, this may expose initiatives in the organization such as a RIF (reduction in Force) inadvertently since AI tools don’t understand how to execute or properly incorporate the concept of timing in employee matters.
Overall, these readings helped me see AI assistants not as a replacement for employee work, but as a carefully governed support tool that requires human literacy, ethical design, and transparent communication. As I read my classmates’ reflections later this week, I’m curious how others are considering the balance between efficiency and responsibility in AI integration, and what they believe organizations owe employees when deploying such tools.
Can Feedback Elevate the Quality of Online Learning?
Reference:
Ertmer, P. A., Richardson, J. C., Belland, B., Camin, D., Connolly, P., Coulthard, G., Lei, K., & Mong, C. (2007). Using peer feedback to enhance the quality of student online postings: An exploratory study. Journal of Computer-Mediated Communication, 12(4), 412–433. https://doi.org/10.1111/j.1083-6101.2007.00331.x
Annotation:
Ertmer et al. (2007) explores whether structured peer feedback can sustain or improve the quality of graduate students’ online discussion posts in a fully online course. Using Bloom’s taxonomy as a scoring rubric, the authors examined students’ perceptions of both giving and receiving feedback and measured changes in posting quality over time. Although peer feedback did not significantly increase scores, it successfully maintained quality levels and fostered deeper reflection, metacognition, and engagement. Students valued instructor feedback more but acknowledged peer feedback as a meaningful mechanism for clarifying thinking, validating ideas, and reinforcing learning.
Ertmer et al. (2007) offer a carefully structured and methodologically transparent case study, especially notable for using a variety of tools like surveys, interviews, and rubric-based scoring. By adopting Bloom’s taxonomy as a consistent evaluation framework, the authors ensured a high degree of face validity, which is something often missing in online-learning research. A major strength lies in how they operationalized “quality” through observable cognitive indicators, rather than relying on self-reports alone. Their mixed-methods approach allowed them to capture both the stability of posting quality (quantitative) and the rich internal reasoning students engaged in while giving feedback (qualitative).
The study’s clarity in describing its procedures, anonymity protections, and reliability checks makes it replicable and trustworthy. Moreover, the article’s discussion is unusually candid about logistical constraints, like delayed feedback cycles, showing an awareness of the real-world instructional design challenges that L&D professionals regularly navigate. Overall, the study stands out for its practical applicability and its nuanced treatment of peer review as both a cognitive and social learning tool.
For Allegiant Professional Resources, where our mission is to elevate workforce learning outcomes for clients and consumers, this study reinforces a core truth: learning quality improves when learners actively evaluate and articulate understanding, not just consume content. Ertmer et al.’s insights support our belief that learning frameworks must move beyond passive LMS modules or gamified environments that prioritize activity over cognition. Giving feedback deepens learning more than receiving it and this study helps us further understand the dynamics of learning to better design effective training programs. Allegiant’s vision for a next-generation corporate learning architecture that uses reflective, socially driven, neurologically aligned pathways to strengthen memory, decision-making, and skill transfer.
As we build frameworks that tailor learning to cognitive profiles, peer-based scaffolding can become a powerful differentiator: it honors neurodiverse strengths such as pattern recognition, deep analysis, or verbal reasoning while fostering equitable, inclusive knowledge construction. This article directly informs the L&D ecosystems we design for clients, where meaningful interaction, self-assessment, and cognitive challenge become cornerstones of higher retention and real-world performance.