Arif Perdana
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arifperdana.net
Arif Perdana
@arifperdana.net
1.5K followers 4.5K following 550 posts
Author | Educator | Speaker | Digital Strategy | Data Science and Analytics | Interested in Philosophy, Photography, Music, Movie, and Tech | An Experienced Academic in Multiple Countries | No Scammers | Posts and Comments are on my own | arifperdana.net
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Arif Perdana @arifperdana.net · Aug 17
See the details here.

academic.oup.com/edited-volum...
Oxford Intersections: Social Media in Society and Culture
Abstract. This work will provide an integrated analysis of social media’s transformative and disruptive power across the global sociocultural landscape. Of
academic.oup.com
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Arif Perdana @arifperdana.net · Aug 17
3/
4. Hyper-personalization, surveillance & public trust

5. Electoral manipulation in the Global South

6. Platform governance & algorithmic transparency

7. Citizen agency, digital literacy & counter-narratives
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Arif Perdana @arifperdana.net · Aug 17
2/ We’re exploring how GenAI is disrupting journalism, public trust, and democratic norms. Topics include:

1. Journalism ethics & AI workflows

2. Algorithmic rec systems & echo chambers

3. AI-driven misinformation & credibility crises
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Arif Perdana @arifperdana.net · Aug 17
1/ CALL FOR PAPERS

As AI reshapes newsrooms, who do we trust for reliable information?

Oxford University Press (OUP) is calling for papers for a special section of the Social Media project: News, Journalism, and Trust in the Age of Generative AI.
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Arif Perdana @arifperdana.net · Jun 9
This is the link to the paper: ml-site.cdn-apple.com/papers/the-i...
ml-site.cdn-apple.com
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Arif Perdana @arifperdana.net · Jun 9
4/ So, AI isn’t really “thinking” yet. It mimics the process, but can’t handle real complexity. Like a kid who memorizes formulas but panics when asked to think beyond the textbook.
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Arif Perdana @arifperdana.net · Jun 9
3/ The result? LRMs perform well on moderately complex tasks, but for very easy or very hard ones, standard models do better. LRMs tend to “overthink” or stop thinking altogether when things get too complex.
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Arif Perdana @arifperdana.net · Jun 9
2/ But as the puzzle gets harder, both end up failing, and strangely, the thoughtful one actually stops thinking earlier. That’s what this study found about LRMs. Using puzzles like the Tower of Hanoi, the researchers tested whether these models can truly reason.
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Arif Perdana @arifperdana.net · Jun 9
1/ Large Reasoning Models (LRMs), advanced versions of ChatGPT is like asking two kids to solve a puzzle. The first one gives an answer right away without much thinking. The second tries to think it through, writing out each step. At first, the thoughtful one seems smarter.
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Arif Perdana @arifperdana.net · May 13
Here is the full paper: www.emerald.com/insight/cont...
Service recovery by AI or human agents: Do failure and strategy context matter? | Emerald Insight
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www.emerald.com
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Arif Perdana @arifperdana.net · May 13
Like a referee with no ego, AI gets the nod when customers mess up, it's quick, fair, and unemotional. But when the company’s at fault, customers want a human touch, someone who owns the mistake and says “sorry” like they mean it.
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Arif Perdana @arifperdana.net · May 7
4/ It’s easier, quicker, and way less stressful for companies dealing with lots of data guests.

arxiv.org/abs/2503.01067
All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning
From a first-principles perspective, it may seem odd that the strongest results in foundation model fine-tuning (FT) are achieved via a relatively complex, two-stage training procedure. Specifically, ...
arxiv.org
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Arif Perdana @arifperdana.net · May 7
3/ It’s super flexible, anyone can arrive anytime, yet things still end up nicely organized by the end of the day. Basically, a data lakehouse mixes the easygoing vibe of a backyard hangout (data lake) with the structured planning of a formal party (data warehouse).
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Arif Perdana @arifperdana.net · May 7
2/ This paper suggests using a "lakehouse" approach, similar to having an open, relaxed backyard barbecue. People (data) show up whenever, chill out anywhere first, and later you casually group them by common interests or conversations.
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Arif Perdana @arifperdana.net · May 7
1/ Think about handling data like throwing a massive party. Traditional ways of organizing data are like carefully planning seats for each guest in advance, slow, inflexible, and stressful if unexpected guests show up.
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Arif Perdana @arifperdana.net · May 4
8/ The future? According to the book, it belongs to those who can pair smart tech with clear direction and a strong sense of identity.
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Arif Perdana @arifperdana.net · May 4
7/ This isn’t just about territory or trade, it’s a battle of systems and worldviews.

The West is at a crossroads. Without rebuilding trust, shared purpose, & bold leadership, its innovation risks becoming pointless. China, though strong, also risks becoming too rigid and controlled.
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Arif Perdana @arifperdana.net · May 4
6/ Geopolitically, China’s model, tight control plus tech dominance, is, according to the book, becoming appealing to some nations. The West still leads in military and economic terms, but it’s losing ground in something deeper: meaning and belief.
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Arif Perdana @arifperdana.net · May 4
5/ Especially from tech leaders. No more pretending neutrality, every tech shapes the world.

Today’s leaders need guts, not just brains.
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Arif Perdana @arifperdana.net · May 4
4/ On leadership, the book argues the West is faltering. Too many play it safe, managers, not true leaders, unwilling to stand for core values. But the world needs more than administrators; it needs vision and moral courage.
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Arif Perdana @arifperdana.net · May 4
3/ Meanwhile, China isn’t just chasing tech, it’s racing ahead with a clear direction. While the West argues and doubts itself, China moves forward with a unified plan. Government, tech sector, and ideology are aligned. The result? Focus and speed the West struggles to match.
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Arif Perdana @arifperdana.net · May 4
2/ That’s the West today, advanced tech, but drifting, having lost the shared values that once gave it direction. Without a map, even the best tools can drive us off a cliff.
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Arif Perdana @arifperdana.net · May 4
This book brilliantly weaves tech, leadership, & geopolitics into one sharp narrative.

1/ The author’s analogy hits hard: imagine having the fastest car in the world, but the driver has no idea where to go.
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Arif Perdana @arifperdana.net · Apr 7
4/ If the answer keeps circling back to the same point, it’s not a real explanation, it’s just a repackaged excuse.

The point is, circular reasoning isn’t just flawed logic, it also blocks clear, deeper understanding. For open, rational conversations, it’s best left behind.
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Arif Perdana @arifperdana.net · Apr 7
3/ These sentences seem to explain something, but they just repeat the original claim, like a TikTok song on loop that goes nowhere.

So how do you spot and break it?

Easy. Ask gently, without judgment:
“Other than ‘that’s just how it is,’ why do you think you’re often late?”