diff --git a/libs/labelbox/src/labelbox/schema/ontology.py b/libs/labelbox/src/labelbox/schema/ontology.py
index 32d5a3884..f6c758faa 100644
--- a/libs/labelbox/src/labelbox/schema/ontology.py
+++ b/libs/labelbox/src/labelbox/schema/ontology.py
@@ -98,7 +98,7 @@ class Classification:
         removed in a future release. Dropdown will also
         no longer be able to be created in the Editor on 3/31/2022.
             
-    A classfication to be added to a Project's ontology. The
+    A classification to be added to a Project's ontology. The
     classification is dependent on the Classification Type.
 
     To instantiate, the "class_type" and "name" parameters must
@@ -125,8 +125,10 @@ class Classification:
         instructions: (str)
         required: (bool)
         options: (list)
+        ui_mode: (str)
         schema_id: (str)
         feature_schema_id: (str)
+        scope: (str)
     """
 
     class Type(Enum):
@@ -138,6 +140,10 @@ class Type(Enum):
     class Scope(Enum):
         GLOBAL = "global"
         INDEX = "index"
+    
+    class UIMode(Enum):
+        HOTKEY = "hotkey"
+        SEARCHABLE = "searchable"
 
     _REQUIRES_OPTIONS = {Type.CHECKLIST, Type.RADIO, Type.DROPDOWN}
 
@@ -149,6 +155,7 @@ class Scope(Enum):
     schema_id: Optional[str] = None
     feature_schema_id: Optional[str] = None
     scope: Scope = None
+    ui_mode: Optional[UIMode] = None # How this classification should be answered (e.g. hotkeys / autocomplete, etc)
 
     def __post_init__(self):
         if self.class_type == Classification.Type.DROPDOWN:
@@ -180,6 +187,7 @@ def from_dict(cls, dictionary: Dict[str, Any]) -> Dict[str, Any]:
                    instructions=dictionary["instructions"],
                    required=dictionary.get("required", False),
                    options=[Option.from_dict(o) for o in dictionary["options"]],
+                   ui_mode=cls.UIMode(dictionary["uiMode"]) if "uiMode" in dictionary else None,
                    schema_id=dictionary.get("schemaNodeId", None),
                    feature_schema_id=dictionary.get("featureSchemaId", None),
                    scope=cls.Scope(dictionary.get("scope", cls.Scope.GLOBAL)))
@@ -198,6 +206,9 @@ def asdict(self, is_subclass: bool = False) -> Dict[str, Any]:
             "schemaNodeId": self.schema_id,
             "featureSchemaId": self.feature_schema_id
         }
+        if (self.class_type == self.Type.RADIO or self.class_type == self.Type.CHECKLIST) and self.ui_mode:
+            # added because this key does nothing for text so no point of including
+            classification["uiMode"] = self.ui_mode.value
         if is_subclass:
             return classification
         classification[
diff --git a/libs/labelbox/tests/unit/test_unit_ontology.py b/libs/labelbox/tests/unit/test_unit_ontology.py
index 82c709663..ac53827c6 100644
--- a/libs/labelbox/tests/unit/test_unit_ontology.py
+++ b/libs/labelbox/tests/unit/test_unit_ontology.py
@@ -2,6 +2,7 @@
 
 from labelbox.exceptions import InconsistentOntologyException
 from labelbox import Tool, Classification, Option, OntologyBuilder
+from itertools import product
 
 _SAMPLE_ONTOLOGY = {
     "tools": [{
@@ -46,6 +47,8 @@
                 "nested classification",
             "type":
                 "radio",
+            'uiMode': 
+                "searchable",
             "options": [{
                 "schemaNodeId":
                     None,
@@ -120,6 +123,8 @@
             "radio",
         "scope":
             "global",
+        'uiMode': 
+            "searchable",
         "options": [{
             "schemaNodeId": None,
             "featureSchemaId": None,
@@ -148,6 +153,11 @@ def test_create_classification(class_type) -> None:
     c = Classification(class_type=class_type, name="classification")
     assert (c.class_type == class_type)
 
+@pytest.mark.parametrize("ui_mode_type, class_type", list(product(list(Classification.UIMode), list(Classification.Type))))
+def test_create_classification_with_ui_mode(ui_mode_type, class_type) -> None:
+    c = Classification(name="classification", class_type=class_type, ui_mode=ui_mode_type)
+    assert (c.ui_mode == ui_mode_type)
+
 
 @pytest.mark.parametrize("value, expected_value, typing",
                          [(3, 3, int), ("string", "string", str)])