Human or AI? 20 Tools to Know Instantly

‍Can You Tell if It's Human or AI?

AI has advanced so much that it's often hard to tell who (or what) you’re interacting with. Ever had a chat or support phone call wondering, “Am I talking to a human or AI?” That’s how powerful today’s AI-powered support tools have become. It goes same with written content, images, videos, and reviews. They look so authentic that you can't decide whether they are original or AI generated.

The same goes for written content; sometimes it’s nearly impossible to know whether it was created by a person or generated by artificial intelligence. In this article, we’ve gathered handy tools and smart technics to help you figure out whether you're dealing with a human or AI.

Let’s begin!

Human or Not – The Fun Guessing Game

There are two popular online games that test your ability to tell the difference between a human and an AI.

The concept is simple: chat with a system for two minutes on any topic, then guess whether you were talking to a real person or an AI bot.

The answer is revealed instantly, and best of all, it’s free to play as many times as you like. We tried both and here’s our take:

1. HumanOrNot.ai

App.HumanOrNot.ai
This version is relatively easier to crack. A few clues? Real humans usually take a bit longer to respond, and you might notice small spelling or grammar mistakes, something AI rarely slips up on.

2. HumanOrNot.so

HumanOrNot.so
This one is a real challenge. The AI here is impressively advanced; it mimics human emotions, humor, and even writing rhythm with surprising accuracy. If you're up for a tougher test to guess “human or AI?”, this is the one to try.

Give them a go and see if you can spot the difference!

Are Reviews Written by Human or AI?

If you’re a business owner or work in marketing, you already know how powerful reviews can be—they can boost your brand or damage it overnight. Unfortunately, some businesses resort to using AI to generate fake reviews, which is both misleading and unethical. Thankfully, there are several tools available that can help you identify whether reviews are genuinely from real users or AI generated.

3. Fakespot

Overview: Fakespot analyzes product and seller reviews on platforms like Amazon, Yelp, and TripAdvisor to detect fake, bot-generated, or AI-written reviews using natural language processing and reviewer behavior analysis.

Features:

• Grades reviews with A–F reliability scores
• Analyzes seller trustworthiness
• Available as browser extension and mobile app
• Supports multiple shopping platforms

Review: Easy to use, with strong credibility scores. Accuracy: ~80–85%, especially useful for spotting mass-generated or incentivized reviews.
Reference: https://www.fakespot.com/

Pricing: Free

4. ReviewMeta

Overview: ReviewMeta is a tool that filters out potentially fake reviews on Amazon by using statistical modeling, reviewer history, and content analysis to calculate an adjusted product rating.

Features:

• Provides “adjusted rating” after filtering suspicious reviews
• Breaks down unnatural patterns like review bursts or repetition
• Browser extension available
• Supports only Amazon

Review: Great for Amazon-specific users. Accuracy: ~75–80%. Doesn’t detect AI-generated content directly but useful for spotting manipulated reviews.
Reference: https://www.reviewmeta.com/

Pricing: Free

5. DeFake

Overview: DeFake is a research-backed tool that flags AI-generated and bot-generated reviews or content, developed in collaboration with university researchers to analyze writing style, linguistic features, and metadata.

Features:

• Detects deepfake reviews and social media bot content
• Built for research, education, and moderation teams
• Uses stylometry and machine learning
• Works across platforms and languages

Review: Academic-grade detection tool. Accuracy: ~82%, but interface is more technical. Best for research and investigative journalism.
Reference: https://defake.ai/

Pricing: Free (primarily for research and academic use)

Tools to Detect AI Generated Videos

Ever watched a video and questioned whether it was real or AI-generated? These powerful tools can help you find out in seconds.

6. Deepware Scanner

Overview: Deepware Scanner is a free app that detects deepfake videos by analyzing facial inconsistencies, blinking patterns, lip sync, and other AI-generated video anomalies.

Features:

• Scans video files and URLs for deepfake traces
• Flags potential deepfake manipulations in real time
• Supports MP4, MOV, and common formats
• Mobile app available for quick scanning

Review: Good entry-level tool for journalists and casual users. Accuracy: ~75–80%, especially with face-swapped or lip-synced content.
Reference: https://www.deepware.ai/

Pricing: Free

7. Microsoft Video Authenticator

Overview: Microsoft Video Authenticator is a deepfake detection tool developed in partnership with AI Foundation. It scans videos for subtle fading, blending, and edge inconsistencies that may signal synthetic content.

Features:

• Detects deepfake content frame-by-frame
• Measures “confidence score” of AI involvement
• Developed for newsrooms and election integrity
• Not publicly available — offered via partners

Review: High-end tool with strong forensic capabilities. Accuracy: ~90%, but access is restricted to verified organizations.
Reference: https://news.microsoft.com/

Pricing: Free (limited access, only for partners or institutions)

8. Sensity AI

Overview: Sensity AI is an enterprise-grade platform that detects and monitors AI-generated visual threats such as deepfakes, visual impersonation, and video manipulation.

Features:

• Deepfake detection at scale (real-time or batch)
• Monitors public internet and private assets for synthetic content
• Provides alerting, dashboards, and threat classification
• Used by governments, media, and security teams

Review: Industry-leading solution for deepfake detection and visual threat intelligence. Accuracy: ~90–95%, ideal for corporate and legal investigations.
Reference: https://sensity.ai/

Pricing: Enterprise only (custom pricing)

Is Image Original or Generated/Tampered by AI?

In the age of deepfakes and synthetic media, these tools make it easier to spot AI-generated images and distinguish them from authentic ones.

9. Hive AI

Overview: Hive AI offers AI-generated content detection services, including identifying synthetic images, deepfakes, and altered media. It is widely used by social media platforms, advertisers, and news organizations.

Features:

• Detects AI-generated faces, altered images, and deepfakes
  
  
• Supports enterprise-scale API access
  
  
• Offers image moderation and content classification
  
  
• Real-time media analysis at scale
  
  

Review: Enterprise-grade tool with high accuracy and fast processing. Trusted by major tech firms. Accuracy: ~90%+. Not available for individual users.
Reference: https://thehive.ai/

Pricing: Enterprise only (custom pricing)

10. AI or Not

Overview: AI or Not is a simple and accessible tool that helps users determine whether an image is AI-generated or captured in real life, including content from models like Midjourney and DALL·E.

Features:

• Drag-and-drop interface for image analysis
  
  
• Detects content from popular image generators
  
  
• Also includes AI-generated text detection
  
  
• Quick and user-friendly experience
  
  

Review: Great for casual users and content creators. Accuracy: ~80%, especially reliable for synthetic portraits.
Reference: https://www.aiornot.com/

Pricing: Free

11. Illuminarty

Overview: Illuminarty is a web-based tool that detects AI-generated visuals, particularly focusing on manipulated and synthetic images circulating online and on social media.

Features:

• Detects images from DALL·E, Midjourney, Stable Diffusion, etc.
  
  
• Supports JPEG, PNG, and WebP formats
  
  
• Provides probability scores with visual indicators
  
  
• Useful for journalists, researchers, and digital forensics
  
  

Review: Highly visual reports; useful in verifying suspicious images. Accuracy: ~85%. Works well with meme-style and illustrative AI art.
Reference: https://illuminarty.ai/

Pricing: Free + Paid plans for premium features

12. FotoForensics

Overview: FotoForensics is a forensic image analysis tool that helps identify image tampering using techniques like Error Level Analysis (ELA) and metadata inspection.

Features:

• Error Level Analysis (ELA) for image manipulation
  
  
• Metadata and histogram inspection
  
  
• Supports common image formats
  
  
• Long-standing tool in digital forensics community
  
  

Review: Best for forensic-level inspection; not AI-specific but useful for identifying inconsistencies. Accuracy: Depends on user expertise.
Reference: https://fotoforensics.com/

Pricing: Free

Is Content Written by Human or AI?

If you want to ensure your website content is 100% human-written and suspect that writers might be using AI, these tools can help you verify the authenticity.

13. GPTZero

Overview: GPTZero is designed primarily for educators, publishers, and content reviewers to detect AI-generated text. It evaluates writing based on metrics like perplexity and burstiness to determine if it was likely written by a human or AI.

Features:

• Highlights specific sentences likely generated by AI
  
  
• Offers batch file upload and API support
  
  
• Includes document metadata inspection
  
  
• Designed for educational and enterprise use
  
  

Review: Clean UI, good for educators, Accuracy score: ~85%, though sometimes misclassifies well-edited human writing. Best used on longer texts for better accuracy.
Reference: https://gptzero.me/

Pricing: Free plan available; paid plans start at $10/month

14. Crossplag

Overview: Crossplag is a plagiarism and AI content detection platform built for academia and enterprise. It scans text to identify both copied and AI-generated content.

Features:

• Detects AI-generated content using proprietary algorithms
  
  
• Integrates plagiarism checking
  
  
• Works across multiple file types and LMS systems
  
  
• Dashboard for educators and teams
  
  

Review: Useful for universities and research reviewers. Accuracy: ~78%, with moderate false positives. Interface feels more academic than commercial.
Reference: https://crossplag.com/

Pricing: Free trial available; contact sales for institutional pricing

15. Originality.ai

Overview: Originality.ai is built primarily for web publishers and content marketers. Originality.ai detects AI-generated content and checks for plagiarism.

Features:

• Offers the entire website scanning option for AI content
• Supports 30 different languages.
• Team collaboration option is available
• Has a plagiarism check feature 

Review: Easy interface, Simple to use, Accuracy score: 76%, but has a high rate of false positives, i.e, flags human-written content as AI-generated. Reference: https://www.scribbr.com/ai-tools/originality-ai-review 

Pricing: $0.01 per 100 words (pay-as-you-go)

16. Sapling AI Detector

Overview: Sapling AI Detector is a real-time AI content detection tool developed for customer-facing teams, writers, and developers. It leverages statistical models to detect whether the content is AI- or human-written.

Features:

• Provides sentence-level probability scores
  
  
• Offers API for integration into apps and workflows
  
  
• Works with short-form content like emails and chats
  
  
• Minimal UI with quick detection speed
  
  

Review: Lightweight and fast, good for quick checks. Accuracy: ~75%. Best for short-form content but not ideal for long academic documents.
Reference: https://sapling.ai/ai-content-detector

Pricing: Free for basic use; API access available in paid plans

17. Writer.com AI Detector

Overview: Writer.com AI Content Detector is a simple web-based tool designed to check if your content has likely been written using AI. It’s useful for content marketers, editors, and educators.

Features:

• Web-based and easy to use
  
  
• Color-coded highlight system for AI-likely segments
  
  
• No sign-up required
  
  
• Built for quick one-off content checks
  
  

Review: Very simple and beginner-friendly. Accuracy: ~72%, with occasional over-detection of professional human writing.
Reference: https://writer.com/ai-content-detector/

Pricing: Free

18. Copyleaks AI Content Detector

Overview: Copyleaks AI Content Detector is a robust AI and plagiarism detection tool used by schools, enterprises, and publishers. It’s designed to work on all major AI models including GPT-3, GPT-4, and others.

Features:

• Supports multiple languages and file types
  
  
• Sentence-level detection with confidence scores
  
  
• Integrates with LMS and enterprise systems
  
  
• Includes real-time API for automation
  
  

Review: Highly accurate with academic-grade detection. Accuracy: ~85%. One of the most trusted tools for institutional use.
Reference: https://copyleaks.com/ai-content-detector

Pricing: Free plan available; paid plans based on volume or enterprise needs

19. Turnitin AI Detection (for Educators)

Overview: Turnitin has integrated AI writing detection into its plagiarism checker, designed specifically for educational institutions. It helps educators detect AI-generated student submissions, including content from models like ChatGPT and GPT-4.

Features:

• Integrated directly into Turnitin’s plagiarism report
  
  
• Sentence-level highlighting of AI-written content
  
  
• Designed for use in schools, colleges, and universities
  
  
• Supports LMS integration (Canvas, Moodle, Blackboard, etc.)
  
  

Review: Highly trusted in academia, especially for essays and assignments. Accuracy: ~98% on longer texts, though shorter content (under 300 words) may yield lower reliability. Works best when combined with human review.
Reference: https://www.turnitin.com/

Pricing: Institutional license required (custom pricing for schools/universities)

20. ZeroGPT

Overview: ZeroGPT is a widely-used AI content detection tool built to identify whether a piece of text was generated by AI models such as ChatGPT, GPT-4, or others. It’s used by students, teachers, writers, and hiring teams.

Features:

• Highlights AI-generated and human-written sections
• Accepts multiple languages and large word counts
• Offers document upload and plagiarism check
• API available for developers and institutions

Review: Simple UI with decent detection rates for longer content. Accuracy: ~75–80%, may produce false positives on well-written human text. Good for casual and academic use.
Reference: https://www.zerogpt.com/

Pricing: Free for basic use; premium features available in paid plans

Am I talking to a Human or AI in Customer Support?

Have you ever stopped mid-conversation during a customer support call/chat and wondered, “Am I talking to a human or AI?”

It can get awkward (and funny!) if you say, “I’d like to speak to a real human,” only to hear, “I am a human.” 

Some bots are upfront and introduce themselves as virtual assistants, but here’s the twist: many companies today use advanced AI customer support tools (which we’ll cover in the next section) that are so well-designed, it’s genuinely tough to tell the difference.

So, how can you spot whether you're chatting with a real person or an intelligent bot? Here are some practical tricks to help you figure out whether you are talking to a human or AI.

1. Response Time

• AI bots usually reply almost instantly—within a second or two.
  
  
• Humans often take a few extra seconds to read, type, and respond.

2. Tone and Emotion

• Bots tend to sound overly polite, formal, or robotic. Their tone lacks emotional depth or nuance.
  
  
• Humans can express empathy, frustration, humor, or even casual slang, especially in longer chats.

3. Repetitive Phrases

• Bots often repeat the same phrases or answers, especially when asked the same question differently.
  
  
• Humans usually rephrase naturally or provide a more personalized response each time.

4. Perfect Grammar & Punctuation

• Bots generally have flawless grammar, punctuation, and spelling.
  
  
• Humans may make occasional typos or informal grammar choices.
  

5. Understanding of Context

• Bots may struggle with context, jokes, or multi-part questions. They might give generic or unrelated responses.
  
  
• Humans usually understand nuance, sarcasm, and context, and can respond accordingly.

6. Handling Unexpected Questions

• Try asking an off-topic or slightly random question like “What’s your favorite movie?”
  
  
• Bots often steer the conversation back or say, “I didn’t understand that.”
  
  
• Humans may respond playfully or acknowledge the shift in topic.

For Businesses: How to Provide Human-Like Support with AI

Let’s shift to real-world business impact. Are you a business owner or CX leader looking to deliver AI-powered customer support so natural that your customers can’t tell whether they are talking to a human or AI?

At Crescendo.ai, we’ve built an AI system that blends new-edge agentic AI with advanced augmented intelligence to create truly human-like experiences. Our AI chatbots, voice assistants, and automated email support agents are designed with built-in empathy, proactive decision-making, and sentiment analysis. 

They adapt their tone and communication style based on the customer’s emotions in real time.

Beyond tone, the AI understands complex workflows, interprets your knowledgebase, and even learns from past interactions to respond with remarkable human-like precision. 

And when a query requires human intervention, it escalates the case to a live support agent, along with a smart summary and recommended actions, so your team can resolve issues faster and more effectively. 

Technologies Behind the AI that Behaves like Human

Now, let’s come to the most technical part of our “human or AI” article. What are the technologies that enable organizations to deliver human-like customer support using AI? Below is a breakdown of the key AI models, technologies, and architectural components powering these experiences:

1. Large Language Models (LLMs)

Used for: Chatbots, email replies, knowledgebase Q&A, call scripting.

• Popular Models:
  
  
  • GPT-4 / GPT-4o (OpenAI)
    
    
  • Claude 3 (Anthropic)
    
    
  • Gemini 1.5 (Google DeepMind)
    
    
  • Mistral and LLaMA 3 (Meta, open-source)
    
• Functions:
  
  
  • Understand customer intent and context
    
    
  • Generate fluent, tone-appropriate responses
    
    
  • Perform few-shot learning from support examples
    

2. Natural Language Understanding (NLU) Engines

Used for: Intent recognition, entity extraction, sentiment analysis.

• Tech stack:
  
  
  • Transformer-based models like BERT, RoBERTa, DistilBERT
    
    
  • Emotion detection models (e.g., GoEmotions, Text2Emotion)
    
• Open-source options: Rasa NLU, spaCy, Hugging Face models
  

3. Speech Recognition + Voice Synthesis

Used for: AI voice agents and call centers.

• ASR (Automatic Speech Recognition):
  
  
  • Whisper (OpenAI)
    
    
  • DeepSpeech (Mozilla)
    
    
  • Google Cloud Speech-to-Text
    
    
• TTS (Text-to-Speech):
  
  
  • ElevenLabs, PlayHT, Amazon Polly, Google TTS
    
    
  • Voice cloning with Tacotron 2, VITS, or Valle
    

4. Sentiment & Emotion Analysis

Used for: Adapting tone, prioritizing tickets, escalation.

• Models used:
  
  
  • Fine-tuned LLMs or transformer models trained on emotion-labeled datasets (e.g., GoEmotions)
    
    
  • Custom classifiers built on top of BERT, RoBERTa
    
• Tools:
  
  
  • AWS Comprehend, Crescendo.ai, IBM Watson Tone Analyzer, OpenAI Function calling with emotion parsing
    

5. Retrieval-Augmented Generation (RAG)

Used for: Answering complex queries from your internal knowledge base.

• How it works:
  
  
  • Combines an LLM with a vector search engine (like Pinecone, Weaviate, or Elasticsearch)
    
    
  • Fetches relevant documents based on the query and lets the LLM generate a context-aware response
    
    
• Models used: OpenAI GPT, Cohere, LangChain for orchestration
  

6. Memory & Context Management

Used for: Remembering prior interactions, user preferences, and conversation history.

• Technologies:
  
  
  • Long-context transformers (e.g., GPT-4o with 128k+ token memory)
    
    
  • External memory layers with Redis or vector stores
    
    
  • Tools: LangGraph, LlamaIndex, custom memory APIs
    

7. Automated CSAT Scoring & Ticket Classification

Used for: Performance analytics, routing, quality control.

• Approach:
  
  
  • Use LLMs + custom classifiers to analyze tone, length, keywords, resolution success
    
    
  • Label conversations and assign CSAT scores
    
    
• Models: Fine-tuned BERT or LLaMA for classification tasks
  
  

8. Multi-Modal AI (Text + Voice + Image)

Used for: Richer CX interactions across formats.

• Models:
  
  
  • GPT-4o (multi-modal)
    
    
  • Gemini 1.5 (image + audio)
    
    
  • Speech-to-text + LLM + TTS pipelines
    

Bonus: Agentic AI Stack (for autonomous workflows)

Used for: End-to-end support task automation without human input.

• Agent frameworks:
  
  
  
  • AutoGPT, SuperAgent, LangChain Agents, Crescendo's Agentic Layer
    
    
  • Uses LLMs + tools + memory + state tracking to take multi-step actions

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