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{
    "pk": 49986,
    "title": "Increasing effective charitable giving with personalized LLM conversations",
    "subtitle": null,
    "abstract": "Despite substantial charitable giving, donations often fail to maximize impact. While a variety of persuasive strategies can increase donations to effective charities, their success depends on individual differences. Large Language Models (LLMs) offer a powerful solution to this problem by dynamically personalizing persuasive strategies. In a pre-registered experiment (N=1952), we tested whether personalized LLM conversations could increase donations to the Against Malaria Foundation (AMF), rated one of the world's most effective charities. Participants allocated $1 between their favorite charity and AMF after being assigned to either: (1) a personalized persuasive LLM conversation, (2) a static LLM-generated persuasive message, and (3) a control conversation. Personalized LLM conversations significantly increased donations to AMF by 46.6%, outperforming the static message (28.7% increase). Personalized LLMs also shifted moral attitudes about charitable giving. Our findings highlight the potential of AI-driven personalization to enhance effective giving and provide new insights into the psychology of charitable persuasion.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Artificial Intelligence; Psychology; Behavioral Science; Decision making; Human-computer interaction; Social cognition; Computer-based experiment"
        }
    ],
    "section": "Abstracts with Poster Presentation",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/36r0h3mv",
    "frozenauthors": [
        {
            "first_name": "Joshua",
            "middle_name": "P",
            "last_name": "White",
            "name_suffix": "",
            "institution": "Massachusetts Institute of Technology",
            "department": ""
        },
        {
            "first_name": "Carter",
            "middle_name": "",
            "last_name": "Allen",
            "name_suffix": "",
            "institution": "University of California",
            "department": ""
        },
        {
            "first_name": "Lucius",
            "middle_name": "",
            "last_name": "Caviola",
            "name_suffix": "",
            "institution": "University of Oxford",
            "department": ""
        },
        {
            "first_name": "Thomas",
            "middle_name": "",
            "last_name": "Costello",
            "name_suffix": "",
            "institution": "American University",
            "department": ""
        },
        {
            "first_name": "David",
            "middle_name": "",
            "last_name": "Rand",
            "name_suffix": "",
            "institution": "MIT",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2025-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49986/galley/37948/download/"
        }
    ]
}