🧠 Robot Nannies: Indefensible or Inevitable

Subscribe | AI Toolkit | Meet The Team

Welcome back AI prodigies!

In today’s Sunday Special:

• 🦾The Beginning

• 🤖AI Development Doesn’t Care

• ⚔️Pros vs. Cons

• 💨The Latest

• 🔑Key Takeaway

Read Time: 6 minutes

🎓Key Terms

• Anthropomorphism: using human traits, emotions, or intentions to describe non-human entities.

• Deep Learning (DL): an AI technique that mimics the human brain by creating multiple layers of “artificial” neurons to solve problems.

• Graphics Processing Units (GPUs): specialized hardware designed to manage heavy computational workloads through parallel processing (i.e., performing mathematical calculations simultaneously).

• Floating Point Operations Per Second (FLOP/s): the number of addition or multiplication math problems a computer solves.

🩺 PULSE CHECK

🦾THE BEGINNING

Average annual childcare costs range from $5,000 to $17,000 for infants, depending on location. For most parents, hiring a full-time nanny is out of reach. For others, outsourcing childcare outside the family is untenable. As a result, only 12% of parents with children under three and only 9% of parents of children between three and five hire nannies. If you’re reading this, you probably didn’t have a nanny pick you up from school, drive or walk you home, and then feed, entertain, and teach you until your parents came home. But your children might.

Imagine your children returning home from school to a friendly, rotund little robot friend. This rotund little robot friend asks your children about their day while preparing healthy snacks. It then lets them watch TV shows for precisely 45 minutes before homework time. Your children can ask for help with their homework from their rotund little robot friend without being given the answers. If you’re late from work, you won’t have to plead with a nanny to stay a few more hours. Instead, update your rotund little robot friend’s schedule through an app. It’ll continue with further tasks like cooking dinner for your children and sending them off to bed with a bedtime story.

Dystopian? We think so. Far-fetched? Maybe not.

🤖AI DEVELOPMENT DOESN’T CARE

In a recent interview with AI researcher Carl Schulman on the 80,000 Hours podcast, he explained: “Tim Berners-Lee, the inventor of the World Wide Web (WWW), gave an example of AI’s limitations by saying there’ll never be robot nannies. No one would ever want to have a robot take care of their kids.”

This opinion is echoed by most. In 2021, the International Journal of Information Management (IJIM) published a joint paper titled, “What is it about humanity that we can’t give away to intelligent machines?” Unsurprisingly, it highlighted the potential negative impacts of robot nannies on children’s psychological development. Nevertheless, revolutionary technology is often implemented irrespective of its implications; too many Internet-era examples exist. If you told someone ten years ago that in 2024, over half of an entire generation would admit to scrolling on a screen like a gambler on a slot machine for nearly as much time as they spend in class—4.8 hours, on average—they’d have told you, “You’re crazy!”

Schulman thinks we’re all massively underestimating how fast AI develops due to its exponential growth.

Epoch AI, a research institute investigating key trends shaping AI’s trajectory, shows how three critical features of AI development are changing over time.

1. Training Compute: Based on the top 333 models, the number of mathematical operations needed to train a Deep Learning (DL) AI model doubles every six months.

2. Algorithmic Improvements: The physical compute (i.e., the amount of computer hardware) required to achieve a given performance in language models halves every eight months.

3. Computational Performance: The number of Floating Point Operations Per Second (FLOP/s) for Graphics Processing Units (GPUs) requiring 32 computer memory units doubles every 2.3 years. In other words, computer chips that power AI tools like OpenAI’s ChatGPT can do more math with the same brain power.

“So when you combine all these things, the growth of effective computing for training big AI applications is pretty drastic,” Schulman concluded. It’s not whether robot nannies will come to market, but when. We must predict their implications before the time comes.

⚔️PROS VS. CONS

For instance, how could a robot protect your children from danger without restricting their freedom to learn through exploration? According to Schulman, how well humans (e.g., nannies, teachers, or parents) can do that task is questionable. He asserts that robotic systems, at the rate of AI development, could outperform teachers and nannies in learning the child’s preferences and biases. “They’re wittier, funnier, and understand the kid much better. Their thoughts and practices are informed by data from working with millions of other children. Super capable.”

However, could robots hurt children? Unlike humans, “They’re never going to harm or abuse the child; they’re not going to get kind of lazy when the parents are out of sight.” Even if parents are worried about children becoming dependent on their robot nannies, that could be programmed. According to Schulman, parents can set criteria about what they’re optimizing: risks of danger, learning, satisfaction, or how the robot nanny interacts with the parent-child relationship. From his perspective, the upsides are many—high performance by the nanny at all times, availability for care and stimulation, highly personalized tutoring, and continuous individual attention.

Nevertheless, we resent Schulman’s opinion. It feels heartless, callous, and ultimately ineffective. Goodbye to socio-emotional learning. Children’s brain development is not fully understood; tampering with it has known and unknown implications. But public objections likely won’t stop AI’s growth in robot nanny applications.

💨THE LATEST

According to Nick Hawes, professor of AI and robotics in the Department of Engineering Science at Oxford University (OU), there is already massive interest in funding robot nannies. Even though the autonomy and intelligence of humanoid robots are currently limited, Hawes thinks we might see a full-fledged robot nanny within five years. Maybe even sooner in countries like China or Japan, which face a rapidly aging society, where the development of working social robots has been underway for the past decade.

iPal, a child-sized humanoid robot that retails for $2,499, is already “selling like hotcakes” in Asia. It can talk, dance, play games, read stories, and connect to the Internet. It can wake up your children in the morning and remind them to brush their teeth before taking daily medications. It can present engaging lessons and dole out praise with “personality,” learning your children’s likes and dislikes with more usage. For example, iPal’s “Emotion Management System (EMS)” detects your children’s emotions and reacts accordingly.

Some parents embrace the idea of robot nannies playing a supplementary role in parenting by dealing with the more monotonous and laborious tasks, leaving parents to spend more quality time with their children. “My children get love from me. I just need backup support. I’m a single mother with a six-year-old and an eight-year-old. Quite frankly, the idea of a robot nanny is an absolute dream,” wrote Charlotte Cripps, Senior Culture Writer at The Independent.

Despite the early popularity of iPal, the backlash against the idea of robot nannies has been intense. Behavioral science trends have shown “that the lack of authenticity doesn’t matter when it comes to the human response to feigned emotion.” Both adults and children tend to humanize nanny robots as they’re alive and conscious, a process known as anthropomorphism. Humans are hardwired to “anthropomorphize the relevant subjects and objects in one’s environment.” More importantly, humans changed their behaviors and attitudes once they saw non-human objects as “human.”

Social scientists worry that developing these relationships with robot nannies will lead to social decline, especially in children’s emotional growth. As one can imagine, they wouldn’t learn empathy, compassion, and how to read subtle cues from other humans.

Eve Herold, who wrote “Robots And The People Who Love Them,” cites other concerns. Some children act out their inner bully on their robot nannies, hitting and kicking them. Robots won’t fight back, which teaches children that they can bully and abuse without consequences. She also cited long-term brain development research that showed early examples of poor cognitive outcomes among children with electronic toys that exhibited robotic traits. For example, children who played with electronic toys like the famous Sony Aibo Robot Dog showed a decreased quantity and quality of their language skills.

🔑KEY TAKEAWAY

Schulman’s “sci-fi” film vision of robot nannies may be inevitable. It also raises fundamental questions about humanity’s evolution. Why is work structured so parents struggle to care for their children? Why are we seeking technological solutions to human problems instead of turning to our communities? Addictive algorithms have infiltrated most Gen Z minds, sending rates of suicide, depression, and anxiety skyrocketing. Will we learn from the Social Media Era? We must tread cautiously as cutting-edge AI reshapes our social realities. Big Tech companies surely won’t.

📒FINAL NOTE

FEEDBACK

❤️TAIP Review of The Day

REFER & EARN

🎉Your Friends Learn, You Earn!

You currently have 0 referrals, only 1 away from receiving ⚙️Ultimate Prompt Engineering Guide.

Refer 3 friends to learn how to 👷‍♀️Build Custom Versions of OpenAI’s ChatGPT.

Copy and paste this link to friends: https://theaipulse.beehiiv.com/subscribe?ref=PLACEHOLDER