AI and Human Interaction

Artificial Intelligence (AI) stands at the forefront of technological innovation, captivating imaginations with promises of machines rivaling or surpassing human capabilities across various domains. However, amid the excitement and speculation, a discerning eye is required to separate reality from hyperbole. The allure of AI lies in its potential to revolutionize industries, reshape economies, and address global challenges. Yet, historical patterns reveal a cycle of inflated expectations followed by disillusionment—perhaps this provides us the time to better explore the intersection of AI and human interaction.

Professor Ahmed Banafa highlights this cycle in his recent article AI Hype: The Challenges and Realities of Transformative Technology . He argues that throughout history, technological revolutions often come with inflated expectations and grand predictions, from the industrial era to the age of personal computing. Maybe we can tell the hype has reached its peak already with examples like the Oral-B Genius toothbrush boasting AI integration , prompting critics to question if we've gone too far with AI hype.

Some argue that we are already seeing a tapering off. In his recent post, Rudolph Greg Surovcik highlights a leveling off of user expansion among large language models (LLMs) and suggests that the initial wave of adopters may have maxed out. He underscores this by highlighting Ethan Mollick’s notion that it takes considerable time to master these models, which may have dissuaded further uptake. Kandy Vicini highlights that the depletion of data available for AI training raises significant concerns regarding its future direction. She cites a Singularityhub article that highlights a genuine risk that a shortage of training data could impede the speed of AI's advancement. For instance, ChatGPT was trained on 570 gigabytes of text data, while the Stable Diffusion algorithm used a dataset with 5.8 billion image-text pairs. Research suggests that we may run out of high-quality text data before 2026.

However, the potential is still substantial and we will most likely find a way through short-term roadblocks if the upside persists. Steve Rubinow highlights to fully realize these advantages; organizations must address the shortage of AI-specific skills . He highlights a recent collaboration between Access Partnership and Amazon Web Services (AWS) conducted a survey across France, Germany, Spain, and the UK, revealing that 86% of employers anticipate using AI tools by 2028. AI adoption promises significant benefits, including a potential productivity increase of 39% and salary boosts of up to 30%.

Laurie Parma shared a recent study with a client that revealed individuals utilizing AI outperformed those who didn't. By analyzing performance data from quarterly reviews and categorizing employee performance into four tiers, it was evident that AI users showed a higher tendency to exceed performance goals after a six-month period.

Emilio Reyes Le Blanc showcases a company's initiative of sending 50 employees to Microsoft with the aim of exploring AI capabilities through experimentation. The session was divided into two parts: the first focused on understanding AI capabilities, while the latter involved brainstorming ways AI could improve team metrics. He references Bain & Company research indicating that companies with advanced experimentation capabilities tend to adopt artificial intelligence more extensively.

Neil Bhandar highlights that in recent years, AI has consistently outperformed human baselines across various benchmarks. He highlights the latest Stanford AI Index report that demonstrates that AI has surpassed human performance in several benchmarks over the years, including image classification, basic reading comprehension, visual reasoning, and natural language inference. However, it still struggles with more complex cognitive tasks like visual commonsense reasoning and advanced mathematical problem-solving.

Experimenting with Human Interactions

We're currently in the early stages of the AI Age, necessitating crucial decisions at all levels of organizations. Delaying these decisions would mean relinquishing control over them. Experimentation is vital for success, particularly in the face of rapid change. Jeremy Utley provides a contrasting perspective in response to the notion of AI "Recess is over." While experts argue that last year marked AI's coming of age, likening it to a child in school, with this year being for serious work, Utley believes otherwise. He contends that the real experimentation has just started, highlighting that many organizations have yet to even begin their "recess."

?Real experimentation has just started

One potential method to accelerate AI progress is by enhancing human interactions. Jeroen Van Hautte suggests that some AI players may gain an edge due to their access to extensive human-AI interaction data . He illustrates this in his Fortune article with Meta's Llama 3 model, set to integrate AI across WhatsApp, Instagram, and Facebook, potentially reaching over 3 billion users. Meanwhile, companies like OpenAI and Google are leveraging user interaction data to enhance their models. As Meta integrates AI into its platforms, AI interaction feedback becomes more seamless.

Collaboration between humans and AI will be pivotal in navigating this new era

Steve Tate writes a compelling article about the rise of human connection in the age of AI , arguing that as AI becomes more integrated into our lives, our relationship with technology and each other will change. As AI progresses, it may develop its own perspectives, akin to rebellious teenagers. It becomes our responsibility to guide and contextualize AI's growth, akin to parenting. Collaboration between humans and AI will be pivotal in navigating this new era, fostering comprehension, and mitigating risks. Kelley Steven-Waiss of ServiceNow highlights how AI streamlines administrative tasks for managers, freeing up time for meaningful interactions with employees. With AI's help, managers can focus on individual needs and engagement, fostering more positive and impactful manager-employee interactions.

The role of the manager has never been more important. The Worklytics team underscores the significant shifts affecting manager effectiveness , particularly noting the rising prevalence of feelings of isolation among employees. They emphasize low levels of collaboration can contribute to perceptions of isolation within the organization, affecting work visibility and connection. Highlighting the profound impact managers have on both employee experiences and the team.

Isolation is a critical issue in the latest Gallup findings which reveal a concerning trend of disengagement among U.S. employees, with a decline in the satisfaction with organizations, and connection to company mission. The first quarter of 2024 saw engagement drop by three percentage points to 30%, marking the lowest level since 2013. This decline translates to 4.8 million fewer engaged employees. The ratio of engaged to actively disengaged employees also reached its lowest point since 2013.

The ratio of engaged to actively disengaged employees also reached its lowest point since 2013

Rachel Monta?ez HBR's article Fighting Loneliness on Remote Teams highlights the toll of isolation and loneliness, impacting job performance and costing U.S. employers $154 billion yearly. She goes on to demonstrate three types of virtual distance—physical, operational, and affinity that affect remote workers. While leaders may have less influence on physical and operational distance, they can address affinity distance by fostering meaningful connections among team members.

Forcing people back into the office doesn't seem to be the solution. Nick Bloom showcases a study on the ongoing issue of employee frustration regarding the necessity of commuting to the office for tasks that could easily be completed from home is a prominent topic. A survey conducted by SWAA revealed that employees spend approximately 80 minutes engaging in in-person activities during a typical office day, with the remainder of their time allocated to tasks that could be accomplished remotely.

Organizational Network Analysis (ONA) Highlights

Andrew Pitts and Chad Mitchell recently conducted several Organizational Network Analyses (ONAs) for the presenters and authors of the Society for Industrial and Organizational Psychology (SIOP) Annual Conference. Using Polinode to examine historical publications data of all conference presenters, constructing a co-authorship network. The Presenter to Presenter network for SIOP 2024 shows connections between presenters participating in shared events. Each presenter is a node, with the size indicating their total connections. Access the interactive version here.

Starling David Hunter III in a project with his students at Florida Atlantic University, analyzed the pilot episode of the TV series "Empire" . The project emphasized the distinction between formal organizational structure and informal social dynamics, highlighting the insight that the organizational chart does not fully capture the real situation.

Leopoldo Torres Azcona argues that by combining the strengths of human influencers and AI, we can drive better communication, enhance engagement, and foster a more connected workforce. He shares a consulting partner ONA to highlight a common challenge: HR's struggle to effectively communicate across the organization, even with influential catalysts in place. To bridge this gap, leveraging both technology and human expertise is essential for success.

Jeppe Vilstrup Hansgaard shows that when is comes to organizational change, scattered uncommitted individuals pose a significant challenge. However, concentrated clusters of uncommitted people are more manageable. Change leaders must prioritize discussions on organizational commitment's critical role in change success. Without commitment to the organization, individuals are unlikely to embrace or support change initiatives.

Applied Insights

From inflated expectations to practical applications, we're navigating through a pivotal phase in AI's evolution. Here are some things we can each do:

1. Stay Informed: Continuously educate yourself on the latest developments and trends in AI to discern between hype and reality. Follow reputable sources, attend webinars, and participate in relevant forums to stay up-to-date.
2. Invest in AI Skills: Organizations should prioritize upskilling their workforce in AI-specific skills to fully leverage its potential. Offer training programs, workshops, and certifications to employees interested in AI.?
3. Encourage Experimentation: Foster a culture of experimentation within your organization to explore AI capabilities and identify practical applications. Provide resources and support for employees to experiment with AI technologies.
4. Promote Human-AI Collaboration: Emphasize the importance of collaboration between humans and AI in achieving organizational goals. Encourage teams to work alongside AI systems, leveraging their strengths to enhance productivity and performance.
5. Address Employee Connectivity: Recognize and address feelings of isolation among employees, especially in remote work environments. Facilitate virtual team-building activities, promote open communication channels, and provide opportunities for social interaction.
6. Support Manager Effectiveness: Equip managers with the necessary tools and resources to effectively lead teams in the age of AI. Provide training on managing remote teams, fostering employee engagement, and leveraging AI for decision-making.

Join the conversation as we continue to explore the intersection of AI and human interaction in shaping the future of work!

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