5/5 (1)

Like everyone, I have used generative AI in an academic setting for writing papers, to brainstorm ideas, ask basic questions, or even create an image for this specific blog. Upon reflection, I realized I also used it a lot while traveling.

At the start of this year, I went solo-backpacking in Central America for 3 months. As you might know, Spanish is the official language throughout the region (except in Belize), and it’s actually quite uncommon for locals to speak English.

Before setting off, I spent a few months practicing Spanish on Duolingo and followed it up with a three-week language course in Nicaragua when I started travelling. That gave me a solid foundation, but there were many moments where I found myself using the Google translate app. I could take pictures, speak into my phone or type out a text and get a direct translation within seconds. This helped me for basic vocabulary questions but also facilitated things during my Costa Rica/Panama border crossing where I had to sign a 5 page document as well as answering very technical questions during my Nicaragua/Costa Rica border crossing, all in Spanish. I also found myself using it a lot when communicating at shops or bus stops, or when people started small talk with me to know more about myself or my travels.

Honestly, I don’t think I would have felt as comfortable and confident traveling alone without Google translate while not having perfect fluency in Spanish. Safety wise, knowing I could break down the language barrier instantly and understand key information, provided real peace of mind. Plus, having the app gave me more courage to engage with others, especially in those moments when I understood what someone was asking but didn’t have the exact vocabulary to respond.

However, while Google Translate was a huge help, I started noticing how much I relied on it. I wonder if I could have learned more Spanish without it, especially through practicing it more in real life settings and expanding my vocabulary. For instance, instead of gradually learning to decipher menus, I found myself taking a picture and getting an instant translation. Or when I encountered a word that I had learned but forgotten, I skipped the mental effort of recalling it and just looked it up instead.

Additionally, using an intermediate translator does also take out the magic of interacting with others in their own language. I could agree that this is also part of traveling, especially in Central America where English is not as common (a lot less than you expect). Relying too much on a translation tool can take away from the authenticity of those moments, and I can see how it might encourage some travellers to put in less effort when learning the language.

Overall, I think Google Translate (or any translation app) is a great tool, especially for solo travellers, but I’d still recommend putting in the effort to learn the language, it’s really worth it.

No ratings yet.

In the last few years, we have seen an explosive growth in Generative AI tools that have appeared in many different fields and have been used for many different purposes (McKinsey Global Survey, 2024). 

GenAI has now made its appearance in the world of sport and has revolutionised athletic performances. With its ability to analyse large datasets, it gives coaches and athletes a major competitive advantage by providing insights that were previously unattainable (Attri, 2024).

One of the key ways GenerativeAI improves performance is through personalised training programmes. Data from an athlete’s previous training sessions can be processed to discover areas of strength and weakness. It can then generate tailored training regimens, focusing on optimising an athlete’s physical condition, technique, and overall performance. 

These personalised insights can also play a crucial role in injury prevention and recovery. Indeed, GenAI can detect signs of potential injuries before they become serious. It can then recommend adjustments to an athlete’s training routine to mitigate these risks, helping maintain peak performance levels while reducing the likelihood of injury (Moore, 2023). 

Additionally, on another note, GenAI has shown to also increase athletes’ motivation by adding personalised milestones as well as gamification of training (Institute of electrical engineers, 2024). This can be combined as well with all the different aspects mentioned above. For example, creating a personalised and gamified recovery plan for an injured athlete.    

However, after underlining how GenAI might improve athletes’ performances, its disadvantages should be highlighted. These can go from overreliance on technology, to misread injury-related data, ethical concerns about doping, and failing to consider athletes’ mental health (Yang et al., 2024).  

I also personally think that these technological advantages can also widen the gap between large nations/clubs and smaller ones that have fewer resources and access to these technologies. It strengthens the direct correlation between one’s budget and its athletes’ performances, although some argue that this is already the case .  

In conclusion, Generative AI has and will continue to influence the sport industry in many different ways. While it enables athletes to take their performance to the next level and be personally assisted, its negative aspects can impact athletes like it never has before.   

References:

Attri. (2024, January). Beyond the Game: The Rise of Generative AI in Sports Industry. https://attri.ai/blog/beyond-the-game-the-rise-of-generative-ai-in-sports-industry

Biró, A. (2024). Gamification, GenAI and Reinforcement Learning as Motivational Assets in Performance Sports. IEEE. https://doi.org/10.1109/SACI60582.2024.10619802

McKinsey. (2024). The state of AI in 2024: Generative AI’s breakout year. QuantumBlack AI by McKinsey. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-AIs-breakout-year

Moore, M. (2023). Introduction to sport social work. Practice.

Yang, P., Xu, R., & Le, Y. (2024). Factors influencing sports performance: A multi-dimensional analysis of coaching quality, athlete well-being, training intensity, and nutrition with self-efficacy mediation and cultural values moderation. Heliyon, 10(17). https://doi.org/10.1016/j.heliyon.2024.e36646